{% extends 'templates/global/base.md' %} {% block content %} # Help {% if data.FileExists("Filter") %} ## Data filtering The original image data is transferred into sequence data via base calling, which is defined as raw data or raw reads and saved as FASTQ file format, including the sequence of reads and the reads quality information. In Each FASTQ file, every read is described by four lines, listed as follows: ```text @A80GVTABXX:4:1:2587:1979#ACAGTGAT/1 NTTTGATATGTGTGAGGACGTCTGCAGCGTCACCTTTATCGGCCATGGT + BMMTKZXUUUdddddddddddddddddddddddddddadddddd^WYYU ``` Each sequence has 4 lines, the first and third lines are the sequence names (Some fq file will omit the sequence name after the third line "+" in order to save storage space), generated by the sequence analyzer. The second line is the sequence; The fourth line is the sequencing quality value,in which each letter corresponds to each base in the second line.The base quality is equal to ASCII value of the character in line 4 minus 64, e.g. if the ASCII value of c is 99, then its base quality value is 35. Table 1 demonstrates the concise correspondence between sequencing error rate and sequencing quality value. If the sequencing error rate is denoted as E, base quality is denotedas sQ, therelationshipis as followed: ```image url: {{data.ReportRoot}}/md/pic/seqqua_formula.jpg title: seqqua_formula ``` {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Concise correspondence between sequencing error rate and sequencing quality value file: {{data.StaticRoot}}/seqqua_errorRate_cn.txt --- Sequencing error rate(%) Sequencing quality Corresponding characters 1 20 T 0.1 30 ^ 0.01 40 h --- ``` {% set tn = tn + 1%} For more information about the FASTQ format, please visit http://en.wikipedia.org/wiki/FASTQ_format。 {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Filter/[sample].RawReadsClass.xls:Filtering statistics of a single sample --- Items Description n_read_num Reads with N bases more than 5% adapter_read_num Reads with adaptors low_qual_read_num Low quality reads (More than 20% of the bases qualities are lower than 15) clean_read_num The reads amount after filtering ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Data Filtering Statistics Table --- Items Description 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%} {% endif %} ## Assembly {% if data.FileExists("Assemble") or data.FileExists("Assemble_denovo") %} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} cuffcompare position relationship format description --- Priority Code Description 1 = Complete match of intron chain 2 c Contained 3 j Potentially novel isoform or transcription fragments: at least one splice junction is shared with a reference transcript 4 e Single exon transfrag reference exon and at least 10bp of a reference intron, indicating a possible pre-mRNA fragment 5 i A transfrag falling entirely within the reference intron 6 o Generic exonic overlap with a reference transcrip 7 p Possible polymerase run-on fragment (within 2K bases of a reference transcript) 8 r Repeat, currently determined by y looking at the soft-masked refernce sequence and applied to transcripts where at least 50% of the bases are lower case 9 u Unknown, intergenic transcript 10 x Exonic overlap with reference on the opposite strand 11 s An intron of the transfrag overlaps a reference intron on the opposite strand (likely due to read mapping errors) 12 . (.tracking file only, contains multiple classifications) ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Assemble") %} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Statistics of clean data mapped to genome --- Items Description 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 %} {% if data.FileExists("Coding_Capacity") %} ## Coding Ability Prediction {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Coding Capability prediction Result Format Description --- Items Description ID Transcript ID final The final judgement of the RNA type num_coding Number of methods judged to coding RNA num_noncoding Number of methods judged to noncoding RNA swissprot_flag Whether to match to swissprot pfam_flag Whether to match to pfam CNCI_flag Judgment of CNCI coding ability CPC2_flag Judgment of CPC2 coding ability LGC_flagDB_flag Judgment of LGC coding ability DB_flag Whether to compare to protein database(swissprot or pfam) ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} CNCI prediction Result Format Description --- Items Description Transcript_ID Transcript ID index RNA type score Coding ability score start Predicted CDS starting position end Predicted CDS end position length Transcript length ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} CPC prediction Result Format Description --- Items Description ID Transcript ID transcript_length Transcript length peptide_length putative peptide length Fickett_score Fickett TESTCODE score pI putative isoelectric point ORF_integrity the integrity of the orf coding_probability coding probability label coding/noncoding classification label ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} LGC prediction Result Format Description --- Items Description Sequence Name name of transcript sequence ORF Length length of the longest ORF GC Content GC content of the longest ORF Coding Potential Score coding potential score for a transcript, which is protein-coding RNA if greater than 0 or ncRNA if smaller than 0 Coding Label "Coding" represents mRNA and "Noncoding" represents lncRNA pc Probability of ORF in coding sequence pnc Probability of ORF in non-coding sequence fc Stop-codon probability for coding sequence fnc Stop-codon probability in coding sequence ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} swissprot Result Format Description --- Items Description qseqid query sequence id sseqid subject sequence id pident percentage of identical matches length alignment length mismatch number of mismatches gapopen number of gap openings qstart start of alignment in query qend end of alignment in query sstart start of alignment in subject send end of alignment in subject evalue expect value,The smaller the E-value, the better the match.https://www.metagenomics.wiki/tools/blast/evalue bitscore bit score,The higher the bit-score, the better the sequence similarity. ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} pfam Result Format Description --- Items Description target_name The name of the target sequence or profile. target_accession Accession of the target sequence or profile tlen Length of the target sequence or profile query_name Name of the query sequence or profile target_accession Accession of the target sequence or profile qlen Length of the query sequence or profile full_sequence_E_value E-value of the overall sequence/profile comparison (including all domains) full_sequence_score Bit score of the overall sequence/profile comparison (including all domains), inclusive of a null2 bias composition correction to the score full_sequence_bias The biased composition score correction that was applied to the bit score domain_order This domain’s number domain_num The total number of domains reported in the sequence domain_c_Evalue The "conditional E-value", a permissive measure of how reliable this particular domain may be domain_i_Evalue The "independent E-value", the E-value that the sequence/profile comparison would have received if this were the only domain envelope found in it, excluding any others domain_score The bit score for this domain. domain_bias The biased composition (null2) score correction that was applied to the domain bit score. hmm_coord_from The start of the MEA alignment of this domain with respect to the profile, numbered 1..N for a profile of N consensus positions hmm_coord_to The end of the MEA alignment of this domain with respect to the profile, numbered 1..N for a profile of N consensus positions ali_coord_from The start of the MEA alignment of this domain with respect to the sequence, numbered 1..L for a sequence of L residues ali_coord_to The end of the MEA alignment of this domain with respect to the sequence, numbered 1..L for a sequence of L residues env_coord_from The start of the domain envelope on the sequence, numbered 1..L for a sequence of L residues env_coord_to The end of the domain envelope on the sequence, numbered 1..L for a sequence of L residues acc The mean posterior probability of aligned residues in the MEA alignment description_of_target The remainder of the line is the target’s description line ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Quantification") %} ## Quantitative Analysis {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Quantitative Result Format Description --- Items Description 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 ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Express Statistical Result Format Description --- Items Description Sample Sample ID novel_lncRNA.gene The number of novel lncRNA genes novel_mRNA.gene The number of novel mRNA genes novel_lncRNA.isoforms The Number of novel lncRNA transcripts novel_mRNA.isoforms The Number of novel mRNA transcripts known_lncRNA.gene The number of known lncRNA genes known_lncRNA.isoforms The number of known lncRNA transcripts known_mRNA.gene The number of known mRNA genes known_mRNA.isoforms The number of known mRNA genes ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Gene Alignment Statistics Table Format Description --- Items Description 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%} {% endif %} {% if data.FileExists("Coverage") %} ## Gene Coverage Analysis {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Gene Coverage Analysis Result Format Description --- Items Description id Transcript ID length Transcript lenght cov_avg_dep The average coverage depth (Total coverage depth/transcript length) cov_rate Coverage (Total coverage site/transcript length) ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Difference/Group_Diff")%} ## Differences between groups {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Differences Between Groups Statistical Result Format Description --- Items Description Diff Difference scheme known_mRNA The number of all differential known mRNAs known_lncRNA The number of all differential known lncRNAs novel_mRNA The number of all differential novel mRNAs novel_lncRNA The number of all differential novel lncRNAs ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Differences Between Groups Result Format Description --- Items Description 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) ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Difference/Sample_Diff")%} ## Differences between samples {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Differences Between Samples Statistical Result Format Description --- Items Description Diff Difference scheme known_mRNA The number of all differential known mRNAs known_lncRNA The number of all differential known lncRNAs novel_mRNA The number of all differential novel mRNAs novel_lncRNA The number of all differential novel lncRNAs ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Differences Between Samples Result Format Description --- Items Description 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) ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Cluster_Pheatmap") %} ## Cluster analysis File "*.tree_col" and file "*.tree_row" is the corresponding column clustering result and row clustering result, which is recorded in Newick format. Newick format description can refer to : https://en.wikipedia.org/wiki/Newick_format {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Clustering Result Format Description --- Items Description The first column ID The second to last column Gene expression ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Cluster_Mfuzz") %} ## Time series analysis {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Clustering Result Format Description --- Items Description The first column ID The Second column cluster The third column membership The column with the "expstandard_" mark Expression quantity value after standardization The column with the "exp_" mark Expression quantity value ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Cluster_WGCNA") %} ## Co Expression Network Analysis - WGCNA {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} The edges of associated information in Cytoscape format --- Items Description fromNode Source Node Name toNode Target node name weight Weight value of WGCNA direction direction fromAltName Alias of the source node toAltName Alias for target node ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} The node of associated information in Cytoscape format --- Items Description nodeName Node Name altName Node alias nodeAttr Attributes of nodes, module information of WGCNA ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} The correlation coefficient matrix between module and phenotype --- Items Description First row Phenotype name, default to sample name First column Module name, module information for WGCNA Other ranks Correlation coefficient between phenotype and module ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Correlation significance matrix between modules and phenotypes --- Items Description First row Phenotype name, default to sample name First column Module name, module information for WGCNA Other ranks Correlation significance between phenotype and module ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Annotation") %} ## Annotation {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Annotation Statistics Result Format Description --- Items Description 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%} There are two tables with uniform format in the annotation results. One table uses *. merge.xls.gz as the file suffix to record the database annotation information without classification information; A table with *. gene2term.xls.gz as the file suffix is used to record the database annotation information with clear classification information. The two tables are described as follows: {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Annotation Result Format Description 1:Annotation/[database].[tran/gene].merge.xls.gz --- Items Description gene_id/rna_id gene id or rna id [database_name]_desc Annotation of database ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Annotation Result Format Description 2：Annotation/[database].[tran/gene].gene2term.xls.gz --- Items Description gene_id/rna_id gene id or rna id [database_name]_term_id Term ID of database [database_name]_term_desc Term description of database [database_name]_term_level_1 level 1 class of Term [database_name]_term_level_2 level 2 class of Term kgene kgene ID in kegg (The columns unique to kegg are not available in other databases) kgene_name kgene name in kegg (The columns unique to kegg are not available in other databases) kgene_desc kgene description in kegg (The columns unique to kegg are not available in other databases) ``` {% set tn = tn + 1%} Other Annotation Result Format Description: {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Rfam Result Format Description: --- Items Description Family_Name RNA families names Family_Accession RNA families ID RNA RNA ID start The starting position of RNA alignment region end The end position of the RNA alignment region E_value Infernal alignment E value (E value <=0.01) Score Infernal alignment score GC The GC content of the conserved area (%) Rank The rank of the lncRNA in the corresponding family ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} miRNA Precursor Prediction Statistics Result Format Description --- Items Description Query_id query id Anno_Num The number of query mapped to miRNA precursor Anno_Order The Order of query mapped to miRNA precursor Anno_Score The Score of query mapped to miRNA precursor Subject_id subject id Query_Length query length Identity percentage of identical matches Align_length alignment length Miss_match number of mismatches Gap number of gap openings Query_start start of alignment in query Query_end end of alignment in query Subject_start start of alignment in subject Subject_end end of alignment in subject E_value expect value,The smaller the E-value, the better the match Score bit score,The higher the bit-score, the better the sequence similarity ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Rich") or data.FileExists("Rich_target") or data.FileExists("Rich_mfuzz") or data.FileExists("Rich_wgcna") %} ## Enrichment Analysis {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Enrichment Analysis Result Format Description --- Items Description [database_name]_term_id Term ID of database [database_name]_term_candidate_gene_num Number of genes that annotaed to this term in selected gene set(ie. Diffrentially expressed genes) [database_name]_total_candidate_gene_num The total number of genes that can be annotated to database in the selected set [database_name]_term_gene_num Number of genes annotated to this term among all genes of this species [database_name]_total_gene_num The total number of genes that can be annotated to database in this species [database_name]_rich_ratio Enrichment factor value. The ratio of the number of genes annotated to an entry in the selected gene set to the number of genes annotated to the entry in this species. The calculation formula is Rich Ratio = Term Candidate Gene Num / Term Gene Num [database_name]_pvalue Statistical test value (uncorrected) [database_name]_qvalue Pvalue after correction, the significance of judgment is generally based on this value. Generally, it is considered that Qvalue less than 0.05 indicates significance. ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("SnpIndel/SNP") %} ## SNP {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} SNP Statistical Result Format Description --- Items Description sample_name sample name snp_a_g Number of SNPs with A is mutated to G snp_c_t Number of SNPs with C mutated to T snp_transition Number of Transition SNPs snp_a_c Number of SNPs with A is mutated to C snp_a_t Number of SNPs with A is mutated to T snp_c_g Number of SNPs with C mutated to G snp_g_t Number of SNPs with G mutated to T snp_transversion Number of Transversion SNPs snp_total Total number of SNPs ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} SNP Annotation Result Format Description --- Items Description chr Chromosome name pos The starting position of variation id Associated ID ref Reference information alt Mutation information anno Annotation ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("SnpIndel/Indel") %} ## Indel {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} InDel Statistical Result Format Description --- Items Description Sample name Sample name Total number Total number of indel dbsnp rate Proportion of annotation to dbsnp Up2k number of indel that annotate to gene upstream 2k Exon number of indel that annotate to exon Intron number of indel that annotate to intron Down2k number of indel that annotate to gene downtream 2k Intergenic number of indel that annotate to intergenic ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Indel Annotation Result Format Description --- Items Description chr Chromosome name pos The starting position of variation id Associated ID ref Reference information alt Mutation information anno Annotation ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Alternative_Splicing") %} ## Alternative Splicing Analysis {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} A5SS and A3SS Result Format Description --- Items Description 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) ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} MXE Result Format Description --- Items Description 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) ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} RI Result Format Description --- Items Description 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) ``` {% set tn = tn + 1%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} SE Result Format Description --- Items Description 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) ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("GeneFusion") %} ## Gene fusion {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Gene fusion Result Format Description --- Items Description 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 ``` {% set tn = tn + 1%} {% endif %} {% if data.FileExists("Target")%} ## lncRNA Target Gene Prediction {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Cis Result Format Description --- Items Description 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%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Tran Result Format Description --- Items Description 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%} {{data.RenderAnchor("table", tn)}} ```table title: Table{{tn}} Overlap Classification Result description --- Items Description Intronic lncRNA and mRNA are in the same chain, and the lncRNA is completely in the Intron region of the mRNA AntiIntronic lncRNA and mRNA are in the different chains, and the lncRNA is completely in the Intron region of mRNA Overlapping lncRNA and mRNA are in the same chain, and the mRNA is completely in the Intron region of lncRNA AntiOverlapping lncRNA and mRNA are in the different chains, and the mRNA is completely in the Intron region of lncRNA Sense lncRNA and mRNA are in the same chain,Except for intronic and overlapping, lncRNA overlaps with mRNA AntiSense lncRNA and mRNA are in the different chains, except for AntiIntronic and AntiOverlapping, lncRNA overlaps with mRNA ``` {% set tn = tn + 1%} {% endif %} {% endblock %}