{% extends 'templates/global/base.md' %} {% block content %} # Results ## Project Information The basic information of the project is shown as follows: - Project number: {{data.ProjectInfo.ProjectName}} - Product name: {{data.ProjectInfo.ProductNameEN}} - Number of samples: {{ sampleList|length }} - Product type: {{data.ProjectInfo.ProjectType}} - Library type: {{reportDataInfo.LibraryText_en}} - Sequencing platform: {{data.ProjectInfo.SeqPlatform}} - Sequencing length: {{data.ProjectInfo.ReadLength}} - Clean fastq quality score system: {{data.ProjectInfo.FqPhred}} Reference species: - Species name: *{{data.ProjectInfo.SpeciesName}}* {% if data.ProjectInfo.GenomeSource %} - Source: {{data.ProjectInfo.GenomeSource}} - Reference genome version: [{{data.ProjectInfo.GenomeVersion}}]({{data.ProjectInfo.GenomeUrl}}) {% endif %} {% if data.FileExists("Filter") %} ## Data filtering In order to ensure the high quality sequencing data used for subsequent analysis, data filter is the first step. Related results can be found in `Filter/ Filter/`, the file description is as follows: ```tip type: mark title: File description info: File：
    -FilterSummary.xls : Summary of filter statistics of all samples
    -[sample].qual.png : the figure of base quality distribution
    -[sample].base.png : the figure of base distribution
    -[sample].RawReadsClass.xls : Filtering statistics of a sample ``` The statistics of data filtering are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Data Filtering Statistics Table file: {{data.ReportRoot}}/Filter/FilterSummary.xls root: Filter/ --- {{ data.RenderTable("Filter/FilterSummary.xls") }} --- sample_name: sample name total_raw_reads(M): Raw reads number total_clean_reads(M): Clean reads number total_clean_bases(G): Clean reads base number clean_reads_q20(%): Q20 value of clean reads clean_reads_q30(%): Q30 value of clean reads clean_reads_ratio(%): Clean reads ratio ``` {% set tn = tn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList %} {% if not forloop.First %}---{% endif %} title: {{ sample }} url: {{data.ReportRoot}}/Filter/{{sample}}.base.png subTitle: Figure{{fn}} Distribution of Bases desc: Base distribution of display data. X axis: base position of the read, Y axis: base quality, color: base type {% endfor %} ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList %} {% if not forloop.First %}---{% endif %} title: {{ sample }} url: {{data.ReportRoot}}/Filter/{{sample}}.qual.png subTitle: Figure{{fn}} Distribution of Base Quality desc: Base distribution of the display data. X axis: base position of the read, Y axis: base quality {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Assemble_denovo") %} ## Assemble We use Trinity for assembly, and then use cdhit to de-redundant the assembled transcripts. Finally, we used the single-copy direct homologous database BUSCO to evaluate the quality of the assembled transcripts. According to the assembly results, we detected the SSR of the transcript and designed primers. Related results can be found in `Assemble_denovo/ Assemble_denovo/`, the file description is as follows: ```tip type: mark title: File description info: File：
    -All-Unigene.fa: the final assembly result
    -All-Unigene.length.png and All-Unigene.length.txt:Statistical Chart of Assembly Sequence
    -busco_figure.png and BUSCO.stat.xls: Statistical Chart of BUSCO assembly evaluation results
    -[sample]:Statistical chart and assembly result of each sample
    -Folder SSR:the result of SSR ``` Statistics for assembly sequences {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Statistical table of assembly sequences file: {{data.ReportRoot}}/Assemble_denovo/assembly_unigene.stat.xls root: Filter/ --- {{ data.RenderTable("Assemble_denovo/assembly_unigene.stat.xls") }} --- Sample: sample name Total Number: Number of transcripts Total Length: Total length of transcripts Mean Length: Average length of transcripts N50: It is used to measure the continuity of assembly. The larger the value, the better the assembly effect. The calculation method is as follows: when the transcript length is sorted from largest to smallest and accumulated one by one to 50% of the total length of all transcripts, the last accumulated value is N50 N70: Similar to N50 N90: Similar to N50 GC(%): Ratio of base G to base C ``` {% set tn = tn + 1 %} The length distribution of the sequence is as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Assemble_denovo/All-Unigene.length.png subTitle: Figure{{fn}} length distribution of the sequence desc: X axis: the length of transcripts, Y axis: the number of transcripts ``` {% set fn = fn + 1 %} The statistical chart of BUSCO assembly evaluation results is as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Assemble_denovo/busco_figure.png subTitle: Figure{{fn}} statistical chart of BUSCO assembly evaluation desc: BUSCO attempts to provide a quantitative assessment of the completeness in terms of expected gene content of a genome assembly, transcriptome, or annotated gene set. The results are simplified into categories of Complete and single-copy(C), Complete and duplicated(D), Fragmented(F), or Missing(M) BUSCOs. ``` {% set fn = fn + 1 %} The statistical chart of SSR is as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Assemble_denovo/SSR/SSR_statistics.png subTitle: Filter{{fn}} statistical chart of SSR desc: X axis: SSR type，Y axis: SSR number ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Assemble") %} ## Assembly We use HISAT2{{data.RenderReference(1)}} to align the clean reads to the reference genome, and then use StringTie{{data.RenderReference(2)}} to assemble.Finally, the assembly results of all samples are combined with Cuffmerge. Related results can be found in `Assemble/ Assemble/`, the file description is as follows: ```tip type: mark title: File description info: File：
    -RNA_novel_merged.gff3，RNA_novel_merged.gtf，RNA_novel_merged.gff3.psl : gene structure files in three different formats (gff3/psl/gtf)
    -File(\*.stat_tran_num\*.) : statistical table and graph of the number of transcripts corresponding to genes
    -File(\*.stat_tran_len.\*) : statistical table and graph of the length of transcripts corresponding to genes
    -File(\*.stat_exon_num.\*) : statistical table and graph of the number of exon transcripts corresponding to the gene
    -Alignment_hisat.stat.xls : summary table of the genome mapping rate of all samples
    -RNA_novel_merged.fa : Assembled RNA sequence ``` The genome mapping information is as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Statistics of clean data mapped to genome file: {{data.ReportRoot}}/Assemble/Alignment_hisat.stat.xls root: Assemble/ --- {{ data.RenderTable("Assemble/Alignment_hisat.stat.xls") }} --- Sample: sample name TotalCleanReads: The number of clean reads used for mapping TotalMappingRatio: Total mapping ratio UniquelyMappingRatio: Uniquely mapping ratio; When mapping to genome, some reads are mapped to only one position, and some reads are mapped to multiple positions. The statistics here are the ratio of reads that are mapped to only one position. StrandSpecificRatio: Strand specific ratio ``` {% set tn = tn + 1 %} The statistical chart of the novel transcripts is as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Assemble/RNA_novel_merged.stat_exon_num.png subTitle: Figure{{fn}} Distribution of exon numbers desc: The exon numbers distribution of transcripts, including mRNA and lncRNA. X-axis: number of exons, Y-axis: number of transcripts ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Assemble/RNA_novel_merged.stat_tran_len.png subTitle: Figure{{fn}} Distribution of transcripts length desc: The figure shows the length distribution of RNA, including mRNA and lncRNA. X axis: RNA length, Y axis: number of transcripts ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Assemble/RNA_novel_merged.stat_tran_num.png subTitle: Figure{{fn}} Distribution of transcripts number desc: The figure shows the distribution of transcript numbers corresponding to genes, including mRNA and lncRNA. X-axis:transcripts number, Y-axis:number of genes ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Coding_Capacity") %} ## Coding Ability Prediction After obtaining the novel transcript, we will predict the coding ability of the transcript to distinguish between mRNA and lncRNA. We use three predictive softwares and two protein databases. These three softwares are CPC2{{data.RenderReference(3)}}, LGC and CNCI{{data.RenderReference(4)}}.The databases are Pfam{{data.RenderReference(5)}} and SwissProt。 To compare with the Pfam and SwissProt protein databases, we predicted the CDS of the transcripts, translated them into peptides, and then aligned the peptides with Pfam and SwissProt. We used three prediction software: getorf, LongOrfs, and txCdsPredict, to predict the CDS. If all three prediction software were able to predict CDS, then we chose the longest CDS as the final prediction result. Three prediction software were used to score the coding capability of the transcripts, and the lncRNA and mRNA were distinguished according to the scoring threshold. Pfam and SwissProt are protein databases. If the transcript can be aligned with the protein database, it is considered as mRNA, otherwise it is lncRNA. At least three of the five judgment methods have the same prediction results and at least one protein database needs to be aligned , then we can confirm that the transcript is mRNA. Relevant files can be found in `Coding_Capacity/ Coding_Capacity/`, the description of the file is as follows: {% if data.FileExists("Assemble") %} ```tip type: mark title: File description info: File：
    -final.xls ：Summary of coding capacity prediction results
    -novel_mRNA.gtf : Structural information of novel mRNA
    -novel_lncRNA.gtf : Structural information of novel lncRNA
    -final.seq.fa : All Sequences
    -final.mRNA.seq.fa : Sequences of novel mRNA
    -final.lncRNA.seq.fa : Sequences of novel lncRNA
    -final.mRNA.cds.fa : cds of novel mRNA
    -final.mRNA.pep.fa : Protein of novel mRNA
    -File(*.stat_exon_num.*) : Statistical Table and Chart of Exon Number
    -File(*.stat_tran_len.*) : Statistical table and chart of transcript length
    -File(*.stat_tran_num.*) : Statistical table and chart of the number of transcripts corresponding to genes
    -venn : Wayne diagram of different methods    -known_[mRNA/lncRNA].fa : Sequences of known mRNA or lncRNA
    -known_[mRNA/lncRNA].gtf : Structural information of known mRNA or lncRNA
    -ref.stat.xls : Statistics of reference ``` {% endif %} {% if data.FileExists("Assemble_denovo") %} ```tip type: mark title: File description info: File：
    -final.xls ：Summary of coding capacity prediction results
    -final.seq.fa : All Sequences
    -final.mRNA.seq.fa : Sequences of novel mRNA
    -final.lncRNA.seq.fa : Sequences of novel lncRNA
    -final.mRNA.cds.fa : cds of novel mRNA
    -final.mRNA.pep.fa : Protein of novel mRNA
    -venn : Wayne diagram of different methods ``` {% endif %} The Venn diagram of encoding ability prediction is as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Coding_Capacity/venn/noncoding/Venn_Noncoding.png subTitle: Figure{{fn}} Venn Figure of predicted result of LncRNA desc: Display the prediction results of the coding ability in the form of a Venn diagram, and different colors indicate different prediction methods. DB : whether be aligned to Pfam or SwissProt. ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Coding_Capacity/venn/coding/Venn_Coding.png subTitle: Figure{{fn}} Venn Figure of predicted result of mRNA desc: Display the prediction results of the coding ability in the form of a Venn diagram, and different colors indicate different prediction methods. DB : whether be aligned to Pfam or SwissProt. ``` {% set fn = fn + 1 %} The coding capacity prediction results are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} The coding capacity prediction results file: {{data.ReportRoot}}/Coding_Capacity/final.xls root: Coding_Capacity/ --- {{ data.RenderTable("Coding_Capacity/final.xls") }} --- ID: ID of the transcript final: The coding ability judgment num_coding: Number of methods judged to coding RNA num_noncoding: Number of methods judged to noncoding RNA swissprot_flag: Whether align to swissprot pfam_flag: Whether align to pfam CNCI_flag: CNCI judgment on coding ability CPC2_flag: CPC2 judgment on coding ability LGC_flag: LGC judgment on coding ability ``` {% set tn = tn + 1 %} {% if data.FileExists("Assemble") %} {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Statistics of reference file: {{data.ReportRoot}}/Coding_Capacity/ref.stat.xls root: Coding_Capacity/ --- {{ data.RenderTable("Coding_Capacity/ref.stat.xls") }} --- RNA_type: RNA type known_or_novel: known RNA or novel RNA gene_or_transcript: gene or transcript number: rna number ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("Coding_Capacity/novel.stat_exon_num.png") %} The statistics figure for lncRNA and mRNA as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Coding_Capacity/novel.stat_exon_num.png subTitle: Figure{{fn}} Distribution of exon numbers desc: The figure shows the exon numbers distribution in transcripts, including mRNA and lncRNA. X-axis: number of exons, Y-axis: number of transcripts, color: RNA classification ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Coding_Capacity/novel.stat_tran_len.png subTitle: Figure{{fn}} Distribution of transcripts length desc: The statistics figure of RNA length, including mRNA and lncRNA. X-axis: RNA length, Y-axis: number of transcripts, color: RNA classification ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Coding_Capacity/novel.stat_tran_num.png subTitle: Figure{{fn}} Distribution of transcripts number desc: Distribution of the transcripts number of genes, including mRNA and lncRNA, X axis: number of transcripts, Y axis: number of genes, color: RNA classification ``` {% set fn = fn + 1 %} {% endif %} {% endif %} {% if data.FileExists("Quantification") %} ## Quantitative Analysis We use Bowtie2{{data.RenderReference(6)}} to align clean reads to the reference sequence, and then use RSEM{{data.RenderReference(7)}} to calculate the expression of genes and transcripts. Related results can be found in `Quantification/ Quantification/`, the description of the files is as follows: ```tip type: mark title: File description info: File：
    -[sample].gene.Violin.png : Density distribution of gene expression
    -[sample].tran.Violin.png : Density distribution of transcript expression
    -[sample].gene.RSEM.xls : Gene expression
    -[sample].tran.RSEM.xls : Expression of transcripts
    -all.[gene/tran].bar.png : Expression statistics ``` The statistical information of gene expression is as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Gene expression Statistics Table file: {{data.ReportRoot}}/Quantification/exp_info.xls root: Quantification/ --- {{ data.RenderTable("Quantification/exp_info.xls") }} --- sample: sample name known_mRNA.gene: Number of known mRNA genes known_lncRNA.gene: Number of known lncRNA genes novel_mRNA.gene: Number of novel mRNA genes novel_lncRNA.gene: Number of novel lncRNA genes known_mRNA.isoforms: Number of known mRNA transcripts known_lncRNA.isoforms: Number of known lncRNA transcripts novel_mRNA.isoforms: Number of novel mRNA transcripts novel_lncRNA.isoforms: Number of novel lncRNA transcripts ``` {% set tn = tn + 1 %} Gene Alignment statistical information is as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Gene Alignment Statistics Table file: {{data.ReportRoot}}/Quantification/Alignment_bowtie.stat.xls root: Quantification/ --- {{ data.RenderTable("Quantification/Alignment_bowtie.stat.xls") }} --- Sample: sample name TotalCleanReads: The number of clean reads used for mapping TotalMappingRatio: Total mapping ratio(%) UniquelyMappingRatio: Uniquely mapping ratio; When mapping to gene, some reads are mapped to only one position, and some reads are mapped to multiple positions. The statistics here are the ratio of reads that are mapped to only one position.(%) ``` {% set tn = tn + 1 %} {% if data.ProjectInfo.ProjectType == 'DNBSEQ_RNAseq' or data.ProjectInfo.ProjectType == 'DNBSEQ_Strand-specific_RNAseq' %} {% if data.FileExists("Quantification/Alignment_hisat.stat.xls") %} The genome mapping information is as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Statistics of clean data mapped to genome file: {{data.ReportRoot}}/Quantification/Alignment_hisat.stat.xls root: Assemble/ --- {{ data.RenderTable("Quantification/Alignment_hisat.stat.xls") }} --- Sample: sample name TotalCleanReads: The number of clean reads used for mapping TotalMappingRatio: Total mapping ratio UniquelyMappingRatio: Uniquely mapping ratio; When mapping to genome, some reads are mapped to only one position, and some reads are mapped to multiple positions. The statistics here are the ratio of reads that are mapped to only one position. StrandSpecificRatio: Strand specific ratio ``` {% set tn = tn + 1 %} {% endif %} {% endif %} The density distribution of gene level is as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList %} {% if not forloop.First %}---{% endif %} title: {{ sample }} url: {{data.ReportRoot}}/Quantification/{{sample}}.gene.Violin.png subTitle: Figure{{fn}} {{ sample }} gene level expression density graph desc: Here shows the expression levels and densities of mRNA and lncRNA. X axis: RNA density of a certain expression level, Y axis: log10 value of expression level FPKM, color: RNA classification.In the middle there is box plot.From top of the figure there is:the upper quarter, the median (black thick line) and the lower quarter. The median is the number in the middle positions in the data, that is, half of the data is greater than the median (above), and the other half is less than the median (below). A quarter of the data is greater than the upper quartile, which is above the white box; another quarter of the data is less than the lower quartile, which is below the white box. {% endfor %} ``` {% set fn = fn + 1 %} The density distribution of Transcript level is as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList %} {% if not forloop.First %}---{% endif %} title: {{ sample }} url: {{data.ReportRoot}}/Quantification/{{sample}}.tran.Violin.png subTitle: Figure{{fn}} {{ sample }} transcript level expression density graph desc: Here shows the expression levels and densities of mRNA and lncRNA. X axis: RNA density of a certain expression level, Y axis: log10 value of expression level FPKM, color: RNA classification.In the middle there is box plot.From top of the figure there is:the upper quarter, the median (black thick line) and the lower quarter. The median is the number in the middle positions in the data, that is, half of the data is greater than the median (above), and the other half is less than the median (below). A quarter of the data is greater than the upper quartile, which is above the white box; another quarter of the data is less than the lower quartile, which is below the white box. {% endfor %} ``` {% set fn = fn + 1 %} In order to visually show the number of genes in different FPKM range of each sample, we performed statistics on the number of genes in the three cases of FPKM (FPKM<=1, FPKM 1~10, FPKM>=10), as shown in the figure below : {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Quantification/all.tran.bar.png subTitle: Figure{{fn}} Transcript level expression profile desc: The X-axis indicates the sample name, the Y-axis indicates the number of genes, and the shades of color indicate different expression levels of transcript. FPKM <= 1 is a gene with a very low expression level, FPKM between 1and 10 is a gene with a lower expression level, FPKM with> = 10 are high and moderately expressed. ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Quantification/all.gene.bar.png subTitle: Figure{{fn}} Gene level expression profile desc: The X-axis indicates the sample name, the Y-axis indicates the number of genes, and the shades of color indicate different expression levels of transcript. FPKM <= 1 is a gene with a very low expression level, FPKM between 1and 10 is a gene with a lower expression level, FPKM with> = 10 are high and moderately expressed. ``` {% set fn = fn + 1 %} The results of gene levels are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for sample in sampleList %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{sample}} gene level expression file: {{data.ReportRoot}}/Quantification/{{sample}}.gene.RSEM.xls root: Quantification/ --- {{ data.RenderTable(data.Printf("Quantification/%s.gene.RSEM.xls", sample)) }} --- GeneID:gene id TranID:Transcript ID GorT:gene or Transcript Sample:sample RNA_Type:RNA type Read_Count:The number of transcript reads given by RSEM, data has been standardized FPKM:fragments per kilobase of transcript per million fragments mapped TPM:transcripts per million Gene_Length:gene length RSEM_Efective_Gene_Length:Efective Gene Length given by RSEM RSEM_IsoPct:isoform percentage given by RSEM {% endfor %} ``` {% set tn = tn + 1 %} The results of transcript levels are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for sample in sampleList %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{sample}} transcript level expression file: {{data.ReportRoot}}/Quantification/{{sample}}.tran.RSEM.xls root: Quantification/ --- {{ data.RenderTable(data.Printf("Quantification/%s.tran.RSEM.xls", sample)) }} --- GeneID:gene id TranID:Transcript ID GorT:gene or Transcript Sample:sample RNA_Type:RNA type Read_Count:The number of transcript reads given by RSEM, data has been standardized FPKM:fragments per kilobase of transcript per million fragments mapped TPM:transcripts per million Gene_Length:gene length RSEM_Efective_Gene_Length:Efective Gene Length given by RSEM RSEM_IsoPct:isoform percentage given by RSEM {% endfor %} ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("Coverage") %} ## Coverage Analysis We use Bowtie2{{data.RenderReference(6)}} to align clean reads to the reference sequence, and then count the coverage of the transcript. Related results can be found in `Coverage/ Coverage/`, the description of the file is as follows: ```tip type: mark title: File description info: File：
    -[sample].depth.stat.xls：Transcript coverage information of each sample
``` Coverage result is as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for sample in sampleList %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{sample}} transcript coverage file: {{data.ReportRoot}}/Coverage/{{sample}}.depth.stat.xls root: Coverage/ --- {{ data.RenderTable(data.Printf("Coverage/%s.depth.stat.xls", sample)) }} --- id: transcript id length: transcript length cov_avg_dep:The average coverage depth (Total coverage depth/transcript length) cov_rate:Coverage ratio (Total coverage site/transcript length) {% endfor %} ``` {% set tn = tn + 1 %} Gene coverage map is as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList %} {% if not forloop.First %}---{% endif %} title: {{ sample }} url: {{data.ReportRoot}}/Coverage/{{sample}}.png subTitle: Figure {{fn}}: Gene coverage map {{ sample }} desc: The figure shows the coverage of RNA. X axis: gene region, Y axis: gene, color: normalized coverage depth, The yellow color indicates higher coverage depth, the blue color indicates lower coverage depth. {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Difference/Group_Diff")%} ## Differential Gene expression analysis between groups Difference analysis is to compare the expression levels of the samples, excluding expression of genes which is not obvious, and retain the gene with significant differences in expression. A differences analysis between groups is to compare the gene expression of samples in two groups. One is the control group, another is the treated group.Multiple samples can be accepted in one group. We use difference analysis software {{diffMethod}}{{data.RenderReference(8)}} to analyze differences between groups. Related results can be found in `Difference/Group_Diff Difference/Group_Diff`, the file description is as follows: ```tip type: mark title: File description info: File：
    -[diff].gene.[software].xls : Gene difference analysis results of each difference comparison plan
    -[diff].tran.[software].xls : Transcript difference analysis results of each difference comparison plan
    -[diff].gene.[software].Filter.xls : Gene significant difference results
    -[diff].tran.[software].Filter.xls : Transcript significant difference results
    -[diff].[gene/tran].scatter.png : Scatter map of differential genes/transcripts
    -[diff].[gene/tran].volcano.png : volcano map of differential genes/transcripts
    -diff_info_[gene/tran].xls : Statistical information of differential genes ``` The statistical results of differences between groups are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} gene level differences statistics file: {{data.ReportRoot}}/Difference/Group_Diff/Diff_stat_gene.xls root: Difference/ --- {{ data.RenderTable("Difference/Group_Diff/Diff_stat_gene.xls") }} --- Diff:Difference scheme known_lncRNA:The number of all differential known lncRNAs known_mRNA:The number of all differential known mRNAs novel_lncRNA:The number of all differential novel lncRNAs novel_mRNA:The number of all differential novel mRNAs Total: The number of all RNA ``` {% set tn = tn + 1 %} {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} transcript level differences statistics file: {{data.ReportRoot}}/Difference/Group_Diff/Diff_stat_tran.xls root: Difference/Difference/Group_Diff/Diff_stat_tran.xls --- {{ data.RenderTable("Difference/Group_Diff/Diff_stat_tran.xls") }} --- Diff:Difference scheme known_lncRNA:The number of all differential known lncRNAs known_mRNA:The number of all differential known mRNAs novel_lncRNA:The number of all differential novel lncRNAs novel_mRNA:The number of all differential novel mRNAs Total: The number of all RNA ``` {% set tn = tn + 1 %} Statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: gene url: {{data.ReportRoot}}/Difference/Group_Diff/Diff_stat_gene.png subTitle: Figure{{fn}} Difference gene statistics chart between groups desc: X-axis: difference comparison group, Y-axis: RNA number, color: RNA classification --- title: transcript url: {{data.ReportRoot}}/Difference/Group_Diff/Diff_stat_tran.png subTitle: Figure{{fn}} Difference transcript statistics chart between groups desc: X-axis: difference comparison group, Y-axis: RNA number, color: RNA classification ``` {% set fn = fn + 1 %} {% if data.FileExists("Assemble---test") %} 组间差异基因在染色体的统计图如下: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff %} {% if not forloop.First %}---{% endif %} title: 基因水平的{{diff}} url: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.gene.chr_stat.png subTitle: 图{{fn}} {{diff}}组间差异基因在染色体上的分布图 desc: 展示差异基因在染色体上的分布，X轴：染色体，Y轴：RNA数目 {% endfor %} {% for diff in groupDiff %} --- subTitle: 图{{fn}} {{diff}}组间差异基因在染色体上的分布图 desc: 展示差异基因在染色体上的分布，X轴：染色体，Y轴：RNA数目 title: 转录本水平的{{diff}} url: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.tran.chr_stat.png --- {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} Scatter plot: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff %} {% if not forloop.First %}---{% endif %} title: {{diff}} of gene level url: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.gene.scatter.png subTitle: Figure{{fn}} {{diff}} gene level scatter plot desc: The figures showing the distribution of expression levels. X axis: the logarithmic value of genes expression value of a sample, Y axis: the logarithmic value of expression value of another sample in comparision, Color: blue indicates the down-regulated genes, orange indicates the up-regulated genes, brown indicates non-significantly different genes. {% endfor %} {% for diff in groupDiff %} --- title: {{diff}} of transcript level url: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.tran.scatter.png subTitle: Figure{{fn}} {{diff}} transcript level scatter plot desc: The figures showing the distribution of expression levels. X axis: the logarithmic value of genes expression value of a sample, Y axis: the logarithmic value of expression value of another sample in comparision, Color: blue indicates the down-regulated genes, orange indicates the up-regulated genes, brown indicates non-significantly different genes. --- {% endfor %} ``` {% set fn = fn + 1 %} Volcano map: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff %} {% if not forloop.First %}---{% endif %} title: {{diff}} of gene url: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.gene.volcano.png subTitle: Figure{{fn}} {{diff}} gene level volcano map desc: The X-axis represents the fold change of the difference after conversion to log2, and the Y-axis represents the significance value after conversion to-log10. Color:red indicates significantly different gene, grey indicates non-significantly different gene. {% endfor %} {% for diff in groupDiff %} --- title: {{diff}} of transcript level url: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.tran.volcano.png subTitle: Figure{{fn}} {{diff}} transcript level volcano map desc: The X-axis represents the fold change of the difference after conversion to log2, and the Y-axis represents the significance value after conversion to-log10. Color:red indicates significantly different transcript, grey indicates non-significantly different transcript. --- {% endfor %} ``` The results of significantly different genes between groups are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}{{forloop.Counter1}} {{diff}} of gene level file: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.gene.{{diffMethod}}.Filter.xls root: Difference/Group_Diff --- {{ data.RenderTable(data.Printf("Difference/Group_Diff/%s.gene.%s.Filter.xls", diff, diffMethod)) }} --- GeneID:Gene ID TranID:Transcript ID GorT:Gene or Transcript RNA_Type:RNA type Control:Control Case:Case Diff_Flag:Up or down regulation Significant_Difference_Value:Significant level of difference Corrected_Significant_Difference_Value:Corrected difference significance level Fold_Change:Fold Change,log2Ratio(case/control) {% endfor %} ``` {% set tn = tn + 1 %} The results of significantly different transcript between groups are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}{{forloop.Counter1}} {{diff}} of transcript level file: {{data.ReportRoot}}/Difference/Group_Diff/{{diff}}.tran.{{diffMethod}}.Filter.xls root: Difference/Group_Diff --- {{ data.RenderTable(data.Printf("Difference/Group_Diff/%s.tran.%s.Filter.xls", diff, diffMethod)) }} --- GeneID:Gene ID TranID:Transcript ID GorT:Gene or Transcript RNA_Type:RNA type Control:Control Case:Case Diff_Flag:Up or down regulation Significant_Difference_Value:Significant level of difference Corrected_Significant_Difference_Value:Corrected difference significance level Fold_Change:Fold Change,log2Ratio(case/control) {% endfor %} ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("Difference/Sample_Diff")%} ## Differential Gene expression analysis between samples Difference analysis is to compare the expression levels of the samples, excluding the expression of genes which is not obvious, and retaining the gene with significant differences in expression. We use the PossionDis{{data.RenderReference(9)}} method to detect differential genes between samples. Related results can be found in `Difference/Sample_Diff Difference/Sample_Diff`, the file description is as follows: ```tip type: mark title: File description info: File：
    -[diff].gene.[software].xls : Gene difference analysis results
    -[diff].tran.[software].xls : Transcript difference analysis results
    -[diff].gene.[software].Filter.xls : Gene significant difference results
    -[diff].tran.[software].Filter.xls : Transcript significant difference results
    -[diff].[gene/tran].scatter.png : Scatter map of differential genes/transcripts
    -[diff].[gene/tran].volcano.png : volcano map of differential genes/transcripts
    -diff_info_[gene/tran].xls : Statistical information of differential genes ``` The statistical results of differential expression between samples are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Differential expression statistics between samples at the gene level file: {{data.ReportRoot}}/Difference/Sample_Diff/Diff_stat_gene.xls root: Difference/Sample_Diff --- {{ data.RenderTable("Difference/Sample_Diff/Diff_stat_gene.xls") }} --- Diff:Difference scheme known_lncRNA:The number of all differential known lncRNAs known_mRNA:The number of all differential known mRNAs novel_lncRNA:The number of all differential novel lncRNAs novel_mRNA:The number of all differential novel mRNAs Total: The number of all differentially expressed RNA ``` {% set tn = tn + 1 %} {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Differential expression statistics between samples at the transcript level file: {{data.ReportRoot}}/Difference/Sample_Diff/Diff_stat_tran.xls root: Difference/Sample_Diff --- {{ data.RenderTable("Difference/Sample_Diff/Diff_stat_tran.xls") }} --- Diff:Difference scheme known_lncRNA:The number of all differential known lncRNAs known_mRNA:The number of all differential known mRNAs novel_lncRNA:The number of all differential novel lncRNAs novel_mRNA:The number of all differential novel mRNAs Total: The number of all differentially expressed RNA ``` {% set tn = tn + 1 %} Statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: gene url: {{data.ReportRoot}}/Difference/Sample_Diff/Diff_stat_gene.png subTitle: Figure{{fn}} Difference gene statistics chart between samples desc: X-axis:difference comparison sample, Y-axis:RNA number, color:RNA classification --- title: transcript url: {{data.ReportRoot}}/Difference/Sample_Diff/Diff_stat_tran.png subTitle: Figure{{fn}} Difference transcript statistics chart between samples desc: X-axis:difference comparison sample, Y-axis:RNA number, color:RNA classification ``` {% set fn = fn + 1 %} {% if data.FileExists("Assemble---test") %} 样本间差异基因在染色体的统计图如下： {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in sampleDiff %} {% if not forloop.First %}---{% endif %} title: gene:{{diff}} url: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.gene.chr_stat.png subTitle: 图{{fn}} {{diff}}样本间差异基因在染色体上的分布图 desc: 展示差异基因在染色体上的分布，X轴：染色体，Y轴：RNA数目 --- title: isoforms:{{diff}} url: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.tran.chr_stat.png subTitle: 图{{fn}} {{diff}}样本间差异基因在染色体上的分布图 desc: 展示差异基因在染色体上的分布，X轴：染色体，Y轴：RNA数目 {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} Scatter plot: ```image {% for diff in sampleDiff %} {% if not forloop.First %}---{% endif %} title: {{diff}} of gene level url: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.gene.scatter.png subTitle: Figure{{fn}} {{diff}} gene level scatter plot desc: The figures showing the distribution of expression levels. X axis:the logarithmic value of genes expression value of a sample, Y axis:the logarithmic value of expression value of another sample in comparision, Color:blue indicates the down-regulated genes, orange indicates the up-regulated genes, brown indicates non-significantly different genes. --- title: {{diff}} of transcript level url: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.tran.scatter.png subTitle: Figure{{fn}} {{diff}} transcript level scatter plot desc: The figures showing the distribution of expression levels. X axis:the logarithmic value of genes expression value of a sample, Y axis:the logarithmic value of expression value of another sample in comparision, Color:blue indicates the down-regulated genes, orange indicates the up-regulated genes, brown indicates non-significantly different genes. {% endfor %} ``` {% set fn = fn + 1 %} Volcano map: ```image {% for diff in sampleDiff %} {% if not forloop.First %}---{% endif %} title: {{diff}} of gene level url: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.gene.volcano.png subTitle: Figure{{fn}} {{diff}} gene level volcano map desc: The X-axis represents the fold change of the difference after conversion to log2, and the Y-axis represents the significance value after conversion to-log10. Color:red indicates significantly different gene, grey indicates non-significantly different gene. --- title: {{diff}} of transcript level url: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.tran.volcano.png subTitle: Figure{{fn}} {{diff}} transcript level volcano map desc: The X-axis represents the fold change of the difference after conversion to log2, and the Y-axis represents the significance value after conversion to-log10. Color:red indicates significantly different transcript, grey indicates non-significantly different transcript. {% endfor %} ``` {% set fn = fn + 1 %} The results of significantly different genes between samples are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} of gene level file: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.gene.{{diffMethod_sample}}.Filter.xls root: Difference/PossionDis/data/all/gene/{{diff}} --- {{ data.RenderTable(data.Printf("Difference/Sample_Diff/%s.gene.%s.Filter.xls", diff,diffMethod_sample)) }} --- GeneID:Gene ID TranID:Transcript ID GorT:Gene or Transcript RNA_Type:RNA type Control:Control Case:Case Diff_Flag:Up or down regulation Significant_Difference_Value:Significant level of difference Corrected_Significant_Difference_Value:Corrected difference significance level Fold_Change:Fold Change,log2Ratio(case/control) {% endfor %} ``` {% set tn = tn + 1 %} The results of significantly different transcript between samples are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} of transcript level file: {{data.ReportRoot}}/Difference/Sample_Diff/{{diff}}.tran.PossionDis.Filter.xls root: Difference/Sample_Diff --- {{ data.RenderTable(data.Printf("Difference/Sample_Diff/%s.tran.PossionDis.Filter.xls", diff)) }} --- GeneID:Gene ID TranID:Transcript ID GorT:Gene or Transcript RNA_Type:RNA type Control:Control Case:Case Diff_Flag:Up or down regulation Significant_Difference_Value:Significant level of difference Corrected_Significant_Difference_Value:Corrected difference significance level Fold_Change:Fold Change,log2Ratio(case/control) {% endfor %} ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("Cluster_Pheatmap/") %} ## Cluster Analysis In order to find genes with similar expression trends, we use the software pheatmap to cluster the differential genes between groups of different comparison schemes. When clustering multiple samples, we take the union of expression genes. Related results can be found in `Cluster_Pheatmap/ Cluster_Pheatmap/`, the file description is as follows: ```tip type: mark title: File description info: File：
    -[cluster_flag]_all_RNA_[gene/tran].UniID.union.png : Cluster diagram for each cluster plan, gene level and transcript level, respectively.
    -[cluster_flag]_all_RNA_[gene/tran].UniID.xls : The clustering result data of each cluster plan, the ID sequence in the table is consistent with the cluster diagram ``` ```table title: Table{{tn}} cluster plan file: {{data.ReportRoot}}/Cluster_Pheatmap/plan.xls root: Cluster_Pheatmap/ --- {{ data.RenderTable("Cluster_Pheatmap/plan.xls") }} --- Flag: code of cluster plan diff_info: difference plan sample_list: sample list for cluster ``` {% set tn = tn + 1 %} Cluster diagram of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for each_cluster, value in clusterExpInfo %} {% if not forloop.First%}---{% endif %} title:{{each_cluster}} url: {{data.ReportRoot}}/Cluster_Pheatmap/{{each_cluster}}_all_RNA_gene.UniID.union.png subTitle: Figure{{fn}} {{each_cluster}} Cluster diagram desc: Y-axis: RNA, color: cluster value {% endfor %} ``` {% set fn = fn + 1 %} Cluster diagram of transcript level: ```image {% for each_cluster, value in clusterExpInfo %} {% if not forloop.First%}---{% endif %} title:{{each_cluster}} url: {{data.ReportRoot}}/Cluster_Pheatmap/{{each_cluster}}_all_RNA_tran.UniID.union.png subTitle: Figure{{fn}} {{each_cluster}} Cluster diagram desc: Y-axis: RNA, color: cluster value {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Cluster_Mfuzz/") %} ## Time Series Analysis Some genes in the sample will have similar expression patterns at different time points. According to gene expression, it can be clustered into time-related gene clusters, and genes with the same expression pattern will be clustered into one cluster. The analysis software is Mfuzz{{data.RenderReference(26)}}. Related results can be found in `Cluster_Mfuzz/ Cluster_Mfuzz/`, the file description is as follows: ```tip type: mark title: File description info: File：
    -[cluster_flag]_all_RNA_[gene/tran].forCluster.union.png : Cluster diagram for each cluster plan, gene level and transcript level, respectively.
    -[cluster_flag]_all_RNA_[gene/tran]_mfuzz.xls : The clustering result data of each cluster plan ``` {% set tn = tn + 1 %} ```table title: Table{{tn}} cluster plan file: {{data.ReportRoot}}/Cluster_Mfuzz/plan.xls root: Cluster_Mfuzz/ --- {{ data.RenderTable("Cluster_Mfuzz/plan.xls") }} --- Flag: code of cluster plan diff_info: difference plan sample_list: sample list for cluster ``` {% set tn = tn + 1 %} Time series analysis result of gene level: ```image {% for key, value in timeCourseInfo %} {% if not forloop.First%}---{% endif %} title:{{key}} url: {{data.ReportRoot}}/Cluster_Mfuzz/{{key}}_all_RNA_gene.forCluster.union.png subTitle: Figure{{fn}} {{key}} Mfuzz cluster map of gene level desc: The figure shows the results of time series analysis. X-axis: each time point, Y-axis: normalized expression value. Yellow and green correspond to low membership value, red and purple correspond to high membership value root: Cluster_Mfuzz/ {% endfor %} ``` {% set fn = fn + 1%} Time series analysis result of transcript level: ```image {% for key, value in timeCourseInfo %} {% if not forloop.First%}---{% endif %} title:{{key}} url: {{data.ReportRoot}}/Cluster_Mfuzz/{{key}}_all_RNA_tran.forCluster.union.png subTitle: Figure{{fn}} {{key}} Mfuzz cluster map of transcript level desc: The figure shows the results of time series analysis. X-axis: each time point, Y-axis: normalized expression value. Yellow and green correspond to low membership value, red and purple correspond to high membership value root: Cluster_Mfuzz/ {% endfor %} ``` {% set fn = fn + 1%} {% endif %} {% if data.FileExists("Cluster_WGCNA/") %} ## Co Expression Network Analysis - WGCNA WGCNA (Weighted Gene Co expression Network Analysis) is a commonly used method for analyzing gene co expression networks. It can identify the association relationships between genes from large-scale gene expression data and aggregate genes with similar expression patterns into modules. Phenotypic association analysis is also one of the ultimate goals of WGCNA analysis, which can help us identify gene modules and core genes related to phenotypic characteristics. The analysis software is WGCNA. Related results can be found in `Cluster_WGCNA/ Cluster_WGCNA/`, the file description is as follows: ```tip type: mark title: File description info: File：
    -[gene/tran]/[plan]/dissTOM.png : WGCNA clustering module diagram
    -[gene/tran]/[plan]/CytoscapeInput-nodes.txt.gz : Genetic clustering information of WGCNA
    -[gene/tran]/[plan]/WGCNA.ModuleTraitCorSig.png : The correlation between co expressed gene modules and phenotype
    -[gene/tran]/[plan]/dendrogram_module.png : Gene Tree Map and Gene Module ``` {% set tn = tn + 1 %} ```table title: Table{{tn}} WGCNA plan file: {{data.ReportRoot}}/Cluster_WGCNA/plan.xls root: Cluster_Mfuzz/ --- {{ data.RenderTable("Cluster_WGCNA/plan.xls") }} --- Flag: code of WGCNA plan sample_list: sample list for WGCNA ``` {% set tn = tn + 1 %} WGCNA results of gene level: ```image {% for key in reportDataInfo.wgcna_plan_info %} {% if not forloop.First%}---{% endif %} title:{{key}} url: {{data.ReportRoot}}/Cluster_WGCNA/gene/{{key}}/dissTOM.png subTitle: Figure{{fn}} WGCNA Map desc:Display gene networks in the form of heat maps. The lighter the color of the heat map, the higher the correlation between genes. The color blocks along the diagonal are modules. The gene correlation within the same module is very high, while the gene correlation between different modules is much lower. On the left and top of the heat map, there is a gene tree and gene module. root: Cluster_WGCNA/ {% endfor %} ``` {% set fn = fn + 1%} ```image {% for key in reportDataInfo.wgcna_plan_info %} {% if not forloop.First%}---{% endif %} title:{{key}} url: {{data.ReportRoot}}/Cluster_WGCNA/gene/{{key}}/WGCNA.ModuleTraitCorSig.png subTitle: Figure{{fn}} The correlation between co expressed gene modules and phenotype desc:The X-axis represents the phenotype (sample), while the Y-axis represents different co expressed gene modules. The color of the heat map indicates the level of correlation. Pearson correlation coefficient represents the correlation coefficient between modules and samples, and Pvalue represents the significance of the correlation coefficient. root: Cluster_WGCNA/ {% endfor %} ``` {% set fn = fn + 1%} WGCNA results of transcript level: ```image {% for key in reportDataInfo.wgcna_plan_info %} {% if not forloop.First%}---{% endif %} title:{{key}} url: {{data.ReportRoot}}/Cluster_WGCNA/tran/{{key}}/dissTOM.png subTitle: Figure{{fn}} WGCNA Map desc:Display gene networks in the form of heat maps. The lighter the color of the heat map, the higher the correlation between genes. The color blocks along the diagonal are modules. The gene correlation within the same module is very high, while the gene correlation between different modules is much lower. On the left and top of the heat map, there is a gene tree and gene module. root: Cluster_WGCNA/ {% endfor %} ``` {% set fn = fn + 1%} ```image {% for key in reportDataInfo.wgcna_plan_info %} {% if not forloop.First%}---{% endif %} title:{{key}} url: {{data.ReportRoot}}/Cluster_WGCNA/tran/{{key}}/WGCNA.ModuleTraitCorSig.png subTitle: Figure{{fn}} The correlation between co expressed gene modules and phenotype desc:The X-axis represents the phenotype (sample), while the Y-axis represents different co expressed gene modules. The color of the heat map indicates the level of correlation. Pearson correlation coefficient represents the correlation coefficient between modules and samples, and Pvalue represents the significance of the correlation coefficient. root: Cluster_WGCNA/ {% endfor %} ``` {% set fn = fn + 1%} {% endif %} {% if data.FileExists("Annotation") %} ## Annotation In order to better understand gene function, we will annotate the RNA. mRNA annotated databases include:NR,NT,GO,KOG,KEGG,uniprot,COG,PRG,string,TF. lncRNA annotated databases include:miRBase,Rfam. Related results can be found in `Annotation/ Annotation/`, the description of the file is as follows: ```tip type: mark title: File description info: File：
    -[database].[tran/gene].bar.png : Statistical chart of different databases
    -Species_Distribution.png : Species distribution map based on NR annotation information
    -[database].[tran/gene].gene2term.xls.gz : Details of different databases
    -[database].[tran/gene].merge.xls.gz : Details of different databases
    -[mRNA/lncRNA].rfam.aln.xls.gz : Comparison information of rfam
    -lncRNA.blast.miRNA.sort.gz : Alignment information of lncRNA and miRNA precursor sequences
    -TF_sort_blast_anno.xls.gz : Alignment information of mRNA and TF database
    -string.[tran/gene].link.xls.gz : Alignment information of mRNA mRNA and string database ``` {% if data.FileExists("Annotation/Annotation.xls") %} {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Annotation Results Summary Table file: {{data.ReportRoot}}/Annotation/ root: Annotation/data/all --- {{ data.RenderTable("Annotation/")}} --- Type:Statistics at gene level or transcript level kegg_pathway:Genes annotated to the kegg pathway database go_c:Genes annotated to GO cellular component database go_f:Genes annotated to GO molecular function database go_p:Genes annotated to GO biological process database nr:Genes annotated to NR database nt:Genes annotated to NT database uniprot:Genes annotated to uniprot database cog:Genes annotated to cog database kog:Genes annotated to kog database rfam:Genes annotated to rfam database miRBase:Genes annotated to miRBase database ``` {% set tn = tn + 1 %} {% endif %} The annotation statistics are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} annotation statistics file: {{data.ReportRoot}}/Annotation/Anno_stat.xls root: Annotation/ --- {{ data.RenderTable("Annotation/Anno_stat.xls")}} --- Type:Statistics at gene level or transcript level kegg_pathway:RNA annotated to the kegg pathway database go_c:RNA annotated to GO cellular component database go_f:RNA annotated to GO molecular function database go_p:RNA annotated to GO biological process database nr:RNA annotated to NR database nt:RNA annotated to NT database uniprot:RNA annotated to uniprot database cog:RNA annotated to cog database kog:RNA annotated to kog database phi:RNA annotated to phi database string:RNA annotated to string database rfam:RNA annotated to rfam database tf:RNA annotated to transcription factor database miRBase:RNA annotated to miRBase database ``` {% set tn = tn + 1 %} The species statistics are as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Annotation/Species_Distribution.png subTitle: Figure{{fn}} Annotated species statistics desc: The figure shows the species statistics that genes annotated to. color: species ``` {% set fn = fn + 1 %} {{data.RenderHover("GO")}} statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: go of gene level url: {{data.ReportRoot}}/Annotation/go.gene.bar.merge.png subTitle: Figure{{fn}} GO statistical chart desc: X axis:number,Y axis:GO class name --- title: go of transcript level url: {{data.ReportRoot}}/Annotation/go.tran.bar.merge.png subTitle: Figure{{fn}} GO statistical chart desc: X axis:number,Y axis:GO class name ``` {% set fn = fn + 1 %} {{data.RenderHover("KEGG")}} statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: kegg pathway of gene level url: {{data.ReportRoot}}/Annotation/kegg_pathway.gene.bar.merge.png subTitle: Figure{{fn}} KEGG pathway statistical chart desc: X axis:number,Y axis:KEGG pathway class name --- title: kegg pathway of transcript level url: {{data.ReportRoot}}/Annotation/kegg_pathway.tran.bar.merge.png subTitle: Figure{{fn}} KEGG pathway statistical chart desc: X axis:number,Y axis:KEGG pathway class name ``` {% set fn = fn + 1 %} {% if data.FileExists("Annotation/kog.gene.bar.merge.png") %} {{data.RenderHover("KOG")}} statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: KOG of gene level url: {{data.ReportRoot}}/Annotation/kog.gene.bar.merge.png subTitle: Figure{{fn}} KOG statistical chart desc: X axis:number,Y axis:KOG class name --- title: KOG of transcript level url: {{data.ReportRoot}}/Annotation/kog.tran.bar.merge.png subTitle: Figure{{fn}} KOG statistical chart desc: X axis:number,Y axis:KOG class name ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Annotation/cog.gene.bar.merge.png") %} {{data.RenderHover("COG")}} statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: COG of gene level url: {{data.ReportRoot}}/Annotation/cog.gene.bar.merge.png subTitle: Figure{{fn}} COG statistical chart desc: X axis:number,Y axis:COG class name --- title: COG of transcript level url: {{data.ReportRoot}}/Annotation/cog.tran.bar.merge.png subTitle: Figure{{fn}} COG statistical chart desc: X axis:number,Y axis:COG class name ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Annotation/tf.gene.bar.png") %} TF statistical chart: {{ data.RenderAnchor("figure", fn) }} ```image title: TF of gene level url: {{data.ReportRoot}}/Annotation/tf.gene.bar.png subTitle: Figure{{fn}} TF statistical chart desc: X axis:number,Y axis:TF class name --- title: TF of transcript level url: {{data.ReportRoot}}/Annotation/tf.tran.bar.png subTitle: Figure{{fn}} TF statistical chart desc: X axis:number,Y axis:TF class name ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Annotation/lncRNA.rfam.bar.png") %} Rfam statistical chart: ```image title: lncRNA url: {{data.ReportRoot}}/Annotation/lncRNA.rfam.bar.png subTitle: Figure{{fn}} rfam statistical chart with mRNA desc: X axis:number,Y axis:Rfam family name --- title: mRNA url: {{data.ReportRoot}}/Annotation/mRNA.rfam.bar.png subTitle: Figure{{fn}} rfam statistical chart with lncRNA desc: X axis:number,Y axis:Rfam family name --- ``` {% set fn = fn + 1 %} {% endif %} {% endif %} {% if data.FileExists("Target")%} ## lncRNA Target Gene Prediction The function of LncRNA is mainly achieved by cis or trans way acting on the target gene. The function of lncRNA is related to the protein coding gene near cis so as it can serve as a candidate target gene , thus screening the adjacent mRNA of lncRNA as target gene. And tran regulation is not dependent on the location so it will be predicted by calculating the binding energy. If overlap exist on lncRNA and target genes, we will conduct a detailed classification of overlap to understand the details of cis regulation. {{data.RenderReference(15)}}{{data.RenderReference(16)}} Related results can be found in `Target/ Target/`, the description of the files is as follows: ```tip type: mark title: File description info: File：
    -cis.cor.filter.xls : lncRNA Cis Target result
    -cis.cor.filter.stat.* : Overlap classification statistical chart and table
    -tran.cor.filter.xls : lncRNA Tran Target result ``` Overlap classification statistics are as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Target/cis.cor.filter.stat.png subTitle: Figure{{fn}} Overlap classification desc: The figure shows overlap classification. X axis: cis classification, Y axis: number, color: cis classification ``` {% set fn = fn + 1 %} Cis target result as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Cis target result file: {{data.ReportRoot}}/Target/cis.cor.filter.xls root: Target/ --- {{ data.RenderTable("Target/cis.cor.filter.xls") }} --- lncRNA:Transcript ID of lncRNA mRNA:Transcript ID of mRNA lncRNA_class:lncRNA class distance_or_overlap_class:If there is no overlap between lncRNA and target mRNA, the distance between them is given; If overlay exists, the classification of overlap is given lncRNA_chr:Chromosome of lncRNA lncRNA_start:Start position of lncRNA lncRNA_end:End position of lncRNA lncRNA_length:Length of lncRNA lncRNA_chain:Strand of lncRNA mRNA_chr:Chromosome of mRNA mRNA_start:Start position of mRNA mRNA_end:End position of mRNA mRNA_length:Length of mRNA mRNA_chain:Strand of mRNA lncRNA_gene_id:Gene ID of lncRNA mRNA_gene_id:Gene ID of mRNA pearson_rna:Pearson correlation coefficient of transcript level spearman_rna:Spearman correlation coefficient of transcript level pearson_gene:Pearson correlation coefficient of gene level spearman_gene:Spearman correlation coefficient of gene level ``` {% set tn = tn + 1 %} Tran target result as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Tran target result file: {{data.ReportRoot}}/Target/tran.cor.filter.xls root: Target/ --- {{ data.RenderTable("Target/tran.cor.filter.xls") }} --- mRNA:Transcript ID of mRNA lncRNA:Transcript ID of lncRNA mRNA_rnaplex_start_end:mRNA start and end positions of predicted combination area lncRNA_rnaplex_start_end:lncRNA start and end positions of predicted combination area minimum_free_energy:minimum free energy mRNA_gene_id:Gene ID of mRNA lncRNA_gene_id:Gene ID of lncRNA pearson_rna:Pearson correlation coefficient of transcript level spearman_rna:Spearman correlation coefficient of transcript level pearson_gene:Pearson correlation coefficient of gene level spearman_gene:Spearman correlation coefficient of gene level ``` {% set tn = tn + 1 %} {% if data.FileExists("Target/Interaction.xls") %} 基于靶基因预测结果构建的相互作用结果， {{ data.RenderAnchor("table", tn) }} ```table title: 表{{tn}} 靶基因相互作用结果 file: {{data.ReportRoot}}/Target/Interaction.xls root: Target/ --- {{ data.RenderTable("Target/Interaction.xls") }} --- lncRNA: lncRNA的ID mRNA: mRNA的ID total_ratio_lncRNA: total_LE_overlap/lncRNA_length Flag: lncRNA与mRNA（靶基因）间的overlap情况的细致分类 ``` {% set tn = tn + 1 %} {% endif %} {% endif %} {% if data.FileExists("Rich") %} ## Enrichment Analysis of Differential Genes In order to determine the function of the Differential gene, we conduct enrichment analysis of GO and KEGG. Related results can be found in `Rich/ Rich/`, the description of the files is as follows: ```tip type: mark title: File description info: Folder：
    -[diff]: Enrichment results of significantly different genes, including GO enrichment and kegg enrichment
File：
    -[diff]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway].bar.png : Classification statistics
    -[diff]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway].scatter.png：Bubble chart
    -[diff]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_rich_term.xls: Enrichment results ``` Enrichment bubble chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} ``` {% set fn = fn + 1 %} Enrichment bubble chart of transcript level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} ``` {% set fn = fn + 1 %} Annotated GO classification and summary statistics are as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: gene:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of gene level desc: X axis: number; Y axis: class name; Color: class name of top levle --- title: tran:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of transcript level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} {% for diff in sampleDiff%} {% if not forloop.First%}---{% endif %} title: gene:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of gene level desc: X axis: number; Y axis: class name; Color: class name of top levle --- title: tran:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of transcript level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} ``` Statistical chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: all:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of gene level desc: X axis: number; Y axis: class name title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_C.bar.png --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of gene level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of gene level desc: X axis: number; Y axis: class name --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of gene level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_gene_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of gene level desc: X axis: number; Y axis: class name --- {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of transcript level: ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of transcript level desc: X axis: number; Y axis: class name --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich/{{diff}}/{{diff}}_tran_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of transcript level desc: X axis: number; Y axis: class name --- {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Rich_target") %} ## Enrichment Analysis of Differential lncRNA Target Gene In order to determine the function of the Differential lncRNA target gene, we conduct enrichment analysis of GO and KEGG. Related results can be found in `Rich_target Rich_target`, the description of the files is as follows: ```tip type: mark title: File description info: Folder：
    -[diff]: Enrichment results of significantly different genes, including GO enrichment and kegg enrichment
File：
    -[diff]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway].bar.png : Classification statistics
    -[diff]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway].scatter.png：Bubble chart
    -[diff]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_rich_term.xls: Enrichment results ``` Enrichment bubble chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: all:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_C.scatter.png --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} ``` {% set fn = fn + 1 %} Enrichment bubble chart of transcript level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_C.scatter.png --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_C.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_F.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_P.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_kegg_pathway.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} ``` {% set fn = fn + 1 %} Annotated GO classification and summary statistics are as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: gene:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of gene level desc: X axis: number; Y axis: class name; Color: class name of top levle --- title: tran:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of transcript level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} {% for diff in sampleDiff%} {% if not forloop.First%}---{% endif %} title: gene:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of gene level desc: X axis: number; Y axis: class name; Color: class name of top levle --- title: tran:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_GO.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of transcript level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff in groupDiff%} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of gene level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of gene level desc: X axis: number; Y axis: class name --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of gene level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_gene_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of gene level desc: X axis: number; Y axis: class name --- {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of transcript level: ```image {% for diff in sampleDiff%} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of transcript level desc: X axis: number; Y axis: class name --- {% endfor %} {% for diff in sampleDiff%} title: go_C:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_C.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_F.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_go_P.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}} url: {{data.ReportRoot}}/Rich_target/{{diff}}/{{diff}}_tran_kegg_pathway.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of transcript level desc: X axis: number; Y axis: class name --- {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Rich_mfuzz") %} ## Enrichment Analysis of Time Series results In order to determine the function of time deries cluster gene, we conduct enrichment analysis of GO and KEGG. Related results can be found in `Rich_mfuzz Rich_mfuzz`, the description of the files is as follows: ```tip type: mark title: File description info: Folder：
    -[plan]/[cluster]: Enrichment results of Time Series cluster, including GO enrichment and kegg enrichment
File：
    -[plan]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_[cluster].bar.png : Classification statistics
    -[plan]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_[cluster].scatter.png：Bubble chart
    -[plan]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_[cluster]_rich_term.xls: Enrichment results ``` Enrichment bubble chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff, value in timeCourseInfo %} {% for cnum in reportDataInfo.time_course_num %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_go_C_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_go_F_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_go_P_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_kegg_pathway_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} {% endfor %} ``` {% set fn = fn + 1 %} Enrichment bubble chart of transcript level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff, value in timeCourseInfo %} {% for cnum in reportDataInfo.time_course_num %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_go_C_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_go_F_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_go_P_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_kegg_pathway_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} {% endfor %} ``` {% set fn = fn + 1 %} Annotated GO classification and summary statistics are as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff, value in timeCourseInfo %} {% for cnum in reportDataInfo.time_course_num %} {% if not forloop.First%}---{% endif %} title: gene:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_GO_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of gene level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for diff, value in timeCourseInfo %} {% for cnum in reportDataInfo.time_course_num %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_go_C_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_go_F_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_go_P_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of gene level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_gene_kegg_pathway_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of gene level desc: X axis: number; Y axis: class name --- {% endfor %} {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of transcript level: ```image {% for diff, value in timeCourseInfo %} {% for cnum in reportDataInfo.time_course_num %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_go_C_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_go_F_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_go_P_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_mfuzz/{{diff}}/{{cnum}}/{{diff}}_tran_kegg_pathway_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of transcript level desc: X axis: number; Y axis: class name --- {% endfor %} {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("Rich_wgcna") %} ## Enrichment Analysis of WGCNA results In order to determine the function of WGCNA cluster gene, we conduct enrichment analysis of GO and KEGG. Related results can be found in `Rich_wgcna Rich_wgcna`, the description of the files is as follows: ```tip type: mark title: File description info: Folder：
    -[gene/tran]/[plan]/[cluster]: Enrichment results of WGCNA cluster, including GO enrichment and kegg enrichment
File：
    -[plan]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_[cluster].bar.png : Annotated classification statistics at the gene or transcript level
    -[plan]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_[cluster].scatter.png：Enrichment Bubble chart at the gene or transcript level
    -[plan]_[gene/tran]_[GO/go_C/go_F/go_P/kegg_pathway]_[cluster]_rich_term.xls: Enrichment results at the gene or transcript level ``` Enrichment bubble chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for cnum, diff in reportDataInfo.rich_wgcna_plan_info_gene %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_go_C_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_go_F_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_go_P_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_kegg_pathway_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of gene level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} ``` {% set fn = fn + 1 %} Enrichment bubble chart of transcript level: {{ data.RenderAnchor("figure", fn) }} ```image {% for cnum, diff in reportDataInfo.rich_wgcna_plan_info_tran %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_go_C_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_go_F_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_go_P_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} GO Biological Process bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_kegg_pathway_{{cnum}}.scatter.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway bubble chart of transcript level desc: X axis: the enrichment ratio;Y axis: class name;Color:the enriched significance;Size:the number of genes annotated to this class --- {% endfor %} ``` {% set fn = fn + 1 %} Annotated GO classification and summary statistics are as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for cnum, diff in reportDataInfo.rich_wgcna_plan_info_gene %} {% if not forloop.First%}---{% endif %} title: gene:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_GO_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of gene level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} --- {% for cnum, diff in reportDataInfo.rich_wgcna_plan_info_tran %} {% if not forloop.First%}---{% endif %} title: tran:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_GO_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO statistical chart of transcript level desc: X axis: number; Y axis: class name; Color: class name of top levle --- {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of gene level: {{ data.RenderAnchor("figure", fn) }} ```image {% for cnum, diff in reportDataInfo.rich_wgcna_plan_info_gene %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_go_C_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_go_F_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of gene level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_go_P_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of gene level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/gene/{{diff}}/{{cnum}}/{{diff}}_gene_kegg_pathway_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of gene level desc: X axis: number; Y axis: class name --- {% endfor %} ``` {% set fn = fn + 1 %} Statistical chart of transcript level: ```image {% for cnum, diff in reportDataInfo.rich_wgcna_plan_info_tran %} {% if not forloop.First%}---{% endif %} title: go_C:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_go_C_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Cellular Component statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_F:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_go_F_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Molecular Function statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: go_P:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_go_P_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} GO Biological Process statistical chart of transcript level desc: X axis: number; Y axis: class name --- title: kegg_pathway:{{diff}}:{{cnum}} url: {{data.ReportRoot}}/Rich_wgcna/tran/{{diff}}/{{cnum}}/{{diff}}_tran_kegg_pathway_{{cnum}}.bar.png subTitle: Figure{{fn}} {{diff}} KEGG Pathway statistical chart of transcript level desc: X axis: number; Y axis: class name --- {% endfor %} ``` {% set fn = fn + 1 %} {% endif %} {% if data.FileExists("SnpIndel/SNP") %} ## SNP Analysis A Single Nucleotide Polymorphisms (SNPs) is a variation in a single nucleotide(A,T,C&G) that occurs variation at DNA sequences, resulting in the diversity of genomes among species or individuals, including the transitions and transversions of single bases,etc. After mapped to the reference genome, we use the software GATK{{data.RenderReference(13)}} to perform {{data.RenderHover("SNP")}} detection on each sample. For the resulting {{data.RenderHover("SNP")}}, we will target them to specific genes. Related results can be found in `SnpIndel/SNP/ SnpIndel/SNP/`, the description of files is as follows: ```tip type: mark title: File description info: File:
    -[sample].snp.vcf.gz : SNP information of each sample
    -[sample].snp_annot/[sample]_annotation.xls : details of annotation
    -[sample].snp_annot/[sample]_annotation_stat.xls : statistical information of annotation
    -[sample].snp_annot/[sample].element.* : Statistical chart of annotation
``` {{data.RenderHover("SNP")}} statistics results are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} SNP statistics file: {{data.ReportRoot}}/SnpIndel/SNP/SnpSummary.xls root: SnpIndel/SNP/ --- {{ data.RenderTable("SnpIndel/SNP/SnpSummary.xls")}} --- sample_name: Sample name snp_a_g: Number of SNPs where A is mutated to G snp_c_t: Number of SNPs where C is mutated to T snp_transition: Number of SNPs converted snp_a_c: Number of SNPs where A is mutated to C snp_a_t: Number of SNPs where A is mutated to T snp_c_g: Number of SNPs where C is mutated to G snp_g_t: Number of SNPs where G is mutated to T snp_transversion: Number of SNPs to be converted snp_total: The total number of SNPs ``` {% set tn = tn + 1 %} {{data.RenderHover("SNP")}} statistics figure as follows: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/SnpIndel/SNP/SnpSummary.png subTitle: Figure{{fn}} SNP statistics desc: The figure shows SNP statistics result. X-axis: sample, Y-axis: percentage, color: SNP type ``` {% set fn = fn + 1 %} {{data.RenderHover("SNP")}} annotation chart as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList%} {% if not forloop.First%}---{%endif%} title: all:{{sample}} url: {{data.ReportRoot}}/SnpIndel/SNP/{{sample}}.snp_annot/{{sample}}.element.png subTitle: Figure{{fn}} SNP annotation statistics desc: The figure shows SNP annotation statistics results.Color: annotation type. {% endfor %} ``` {% set fn = fn + 1 %} {{data.RenderHover("SNP")}} annotation results as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for sample in sampleList%} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{sample}} SNP annotation results file: {{data.ReportRoot}}/SnpIndel/SNP/{{sample}}.snp_annot/{{sample}}_annotation.xls root: SnpIndel/SNP/data/all/{{sample}}/snp_annot --- {{ data.RenderTable(data.Printf("SnpIndel/SNP/%s.snp_annot/%s_annotation.xls", sample, sample)) }} --- chr: Chromosome name pos: Starting position information of the mutation id: Associated ID information ref: Reference information alt: Mutation information anno: Annotation information {% endfor %} ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("SnpIndel/Indel")%} ## InDel analysis An {{data.RenderHover("InDel")}} (Insertion-Deletion) is the addition or removal of a small number of bases in a DNA sequence. After mapped to the reference genome, we use the software GATK{{data.RenderReference(13)}} to perform {{data.RenderHover("InDel")}} detection on each sample. For the resulting {{data.RenderHover("InDel")}}, we will target them to specific genes. Related results can be found in `SnpIndel/Indel/data/all SnpIndel/Indel/data/all`, the description of the file is as follows: ```tip type: mark title: File description info: File:
    -[sample].indel.vcf.gz : InDel information of each sample
    -[sample].indel_annot/[sample]_annotation.xls : details of annotation
    -[sample].indel_annot/[sample]_annotation_stat.xls : statistical information of annotation
    -[sample].indel_annot/[sample].element.* : Statistical chart of annotation
``` {{data.RenderHover("InDel")}} statistics results are as follows: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} InDel statistics file: {{data.ReportRoot}}/SnpIndel/Indel/IndelSummary.xls root: SnpIndel/Indel/data/all --- {{ data.RenderTable("SnpIndel/Indel/IndelSummary.xls") }} --- Sample name: Sample name Total number: Total number dbsnp rate: The ratio of comments to dbsnp Up2k: Annotate to 2k upstream of the gene Exon: Annotate to exons Intron: Annotate to introns Down2k: Annotate to 2k downstream of the gene Intergenic: Annotate to the intergenic region ``` {% set tn = tn + 1 %} {{data.RenderHover("InDel")}} statistics chart is as follows: {{ data.RenderAnchor("figure", fn) }} ```image {% for sample in sampleList%} {% if not forloop.First%}---{% endif %} title: all:{{sample}} url: {{data.ReportRoot}}/SnpIndel/Indel/{{sample}}.indel_annot/{{sample}}.element.png subTitle: Figure{{fn}} InDel annotation statistics desc: The figure shows Indel annotation statistics result. Color: annotation type. {% endfor %} ``` {% set fn = fn + 1 %} {{data.RenderHover("InDel")}} annotation results are as follows: {{ data.RenderAnchor("table", tn) }} ```table {% for sample in sampleList%} {% if not forloop.First %}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{sample}} InDel annotation result file: {{data.ReportRoot}}/SnpIndel/Indel/{{sample}}.indel_annot/{{sample}}_annotation.xls root: SnpIndel/Indel/data/all/{{sample}}/indel_annot --- {{ data.RenderTable(data.Printf("SnpIndel/Indel/%s.indel_annot/%s_annotation.xls", sample, sample)) }} --- chr: Chromosome name pos: Starting position information of the mutation id: Associated ID information ref: Reference information alt: Mutation information anno: Annotation information {% endfor %} ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("GeneFusion")%} ## Fusion gene detection Gene fusion refers to the process of fusion of all or part of the sequences of two genes into a new gene. We use ericscript to detect the fusion gene of each sample. Related results can be found in `GeneFusion/ GeneFusion/`, the description of the file is as follows: ```tip type: mark title: File description info: File:
    -genefusion_[sample].xls : Fusion gene result
``` The fusion gene details of each sample are shown in the table as follow: {{data.RenderAnchor("table", tn)}} ```table {% for sample in sampleList%} {% if not forloop.First%}+++{% endif %} title: Table{{tn}} {{sample}} fusion genes file: {{data.ReportRoot}}/GeneFusion/genefusion_{{sample}}.xls root: GeneFusion/ --- {{data.RenderTable(data.Printf("GeneFusion/genefusion_%s.xls", sample))}} --- fusion_link_id:Gene fusion number fusion_up_geneid:Upstream fusion gene fusion_up_symbol:Upstream gene name fusion_up_chr:Chromosome of the upstream fusion gene fusion_up_strand:Strand of upstream fusion gene fusion_up_genome_pos:Fusion site of upstream fusion gene fusion_dw_geneid:Downstream fusion gene fusion_dw_symbol:Downstream gene name fusion_dw_chr:Chromosome of the downstream fusion gene fusion_dw_strand:Strand of downstream fusion gene fusion_dw_genome_pos:Fusion site of downstream fusion gene fusion_crossingreads:Inconsistent paired-end reads fusion_spanningreads:Paired-end reads across Junction fusion_fusion_type:Fusion type fusion_ericscore:Fusion score, the higher the score, the more reliable the fusion event is fusion_score_order:Sort {% endfor %} ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Alternative_Splicing") %} ## Alternative Splicing Analysis We use rMATS software to detect alternative splicing events in every samples, and detect differential alternative splicing in different samples. Related results can be found in `Alternative_Splicing/ Alternative_Splicing/`, the description of the files is as follows: ```tip type: mark title: File description info: File：
    -Diff_stat.xls：Differential alternative Splicing Statistics
    -Diff/[diff]/[diff].[A3SS/A5SS/SE/MXE/RI].xls：Differential alternative Splicing result ,include A3SS、A5SS、SE、MXE、RI
    -Sample/[sample]/[sample].[A5SS/A5SS/SE/MXE/RI].xls：Alternative Splicing of sample,include A3SS、A5SS、SE、MXE、RI ``` Differential alternative splicing statistics results: {{ data.RenderAnchor("table", tn) }} ```table title: Table{{tn}} Differential alternative splicing statistics file: {{data.ReportRoot}}/Alternative_Splicing/Diff/Diff_stat.xls root: GeneDiffSplice --- {{ data.RenderTable("Alternative_Splicing/Diff/Diff_stat.xls") }} --- Diff: differential plan A3SS: Number of differential A3SS A5SS: Number of differential A5SS MXE: Number of differential MXE RI: Number of differential RI SE: Number of differential SE ``` {% set tn = tn + 1 %} Differential alternative splicing statistics chart: {{ data.RenderAnchor("figure", fn) }} ```image url: {{data.ReportRoot}}/Alternative_Splicing/Diff/Diff_stat.png subTitle: Figure{{fn}} Differential alternative splicing statistics desc: X axis: differential plan,Y axis:differential alternative splicing number,color:alternative splicing type ``` {% set fn = fn + 1 %} {{ data.RenderAnchor("table", tn) }} Differential alternative splicing results of differential group: ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} A3SS result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/A3SS.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/A3SS.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_longexonstart_0base:Start position of longer exon as_longexonend:End position of longer exon as_shortes:Start position of shorter exon as_shortee:End position of shorter exon as_flankinges:Start position of the exon near the differential exon as_flankingee:End position of the exon near the differential exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} A5SS result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/A5SS.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/A5SS.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_longexonstart_0base:Start position of longer exon as_longexonend:End position of longer exon as_shortes:Start position of shorter exon as_shortee:End position of shorter exon as_flankinges:Start position of the exon near the differential exon as_flankingee:End position of the exon near the differential exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} SE result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/SE.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/SE.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_exonstart_0base:Start position of the skipped exon as_exonend:End position of the skipped exon as_upstreames:Start position of upstream exon as_upstreamee:End position of upstream exon as_downstreames:Start position of downstream exon as_downstreamee:End position of downstream exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} RI result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/RI.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/RI.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_riexonstart_0base:Start position of intron containing exon as_riexonend:Start position of intron containing exon as_upstreames:Start position of upstream exon as_upstreamee:End position of upstream exon as_downstreames:Start position of downstream exon as_downstreamee:End position of downstream exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in groupDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} MXE result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/MXE.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/MXE.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_1stexonstart_0base:Start position of the first exon as_1stexonend:End position of the first exon as_2ndexonstart_0base:Start position of the second exon as_2ndexonend:End position for the second exon as_upstreames:Start position of upstream exon as_upstreamee:End position of upstream exon as_downstreames:Start position of downstream exon as_downstreamee:End position of downstream exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} {{ data.RenderAnchor("table", tn) }} Differential alternative splicing results of differential samples: ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} A3SS result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/A3SS.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/A3SS.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_longexonstart_0base:Start position of longer exon as_longexonend:End position of longer exon as_shortes:Start position of shorter exon as_shortee:End position of shorter exon as_flankinges:Start position of the exon near the differential exon as_flankingee:End position of the exon near the differential exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} A5SS result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/A5SS.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/A5SS.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_longexonstart_0base:Start position of longer exon as_longexonend:End position of longer exon as_shortes:Start position of shorter exon as_shortee:End position of shorter exon as_flankinges:Start position of the exon near the differential exon as_flankingee:End position of the exon near the differential exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} SE result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/SE.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/SE.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_exonstart_0base:Start position of the skipped exon as_exonend:End position of the skipped exon as_upstreames:Start position of upstream exon as_upstreamee:End position of upstream exon as_downstreames:Start position of downstream exon as_downstreamee:End position of downstream exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} RI result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/RI.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/RI.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_riexonstart_0base:Start position of intron containing exon as_riexonend:Start position of intron containing exon as_upstreames:Start position of upstream exon as_upstreamee:End position of upstream exon as_downstreames:Start position of downstream exon as_downstreamee:End position of downstream exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} ```table {% for diff in sampleDiff %} {% if not forloop.First%}+++{% endif %} title: Table{{tn}}.{{forloop.Counter}} {{diff}} MXE result file: {{data.ReportRoot}}/Alternative_Splicing/Diff/{{diff}}/MXE.MATS.JCEC.xls root: GeneDiffSplice --- {{ data.RenderTable(data.Printf("Alternative_Splicing/Diff/%s/MXE.MATS.JCEC.xls", diff)) }} --- gene_id:Gene id gene_symbol:Gene name as_chr:Chromosome as_strand:Strand of the gene as_1stexonstart_0base:Start position of the first exon as_1stexonend:End position of the first exon as_2ndexonstart_0base:Start position of the second exon as_2ndexonend:End position for the second exon as_upstreames:Start position of upstream exon as_upstreamee:End position of upstream exon as_downstreames:Start position of downstream exon as_downstreamee:End position of downstream exon as_ijc_sample_1:Inclusion counts for sample 1. Replicates are comma separated as_sjc_sample_1:Skipping counts for sample 1. Replicates are comma separated as_ijc_sample_2:Inclusion counts for sample 2. Replicates are comma separated as_sjc_sample_2:Skipping counts for sample 2. Replicates are comma separated as_incformlen:Length of inclusion form, used for normalization as_skipformlen:Length of skipping form, used for normalization as_pvalue:Significance of splicing difference between the two sample groups as_fdr:False Discovery Rate calculated from p-value as_inclevel1:Inclusion level for sample 1. Replicates are comma separated. Calculated from normalized counts as_inclevel2:Inclusion level for sample 2. Replicates are comma separated. Calculated from normalized counts as_incleveldifference:average(IncLevel1) - average(IncLevel2) {% endfor %} ``` {% set tn = tn + 1 %} {% endif %} {% if data.FileExists("custom")%} TODO 文件浏览器 {% endif %} ## References {{ data.RenderReferenceFoot() }} {% endblock %}