a0c54bf7aecca671af8fa6063e129e7524302ca3 gperez2 Tue Feb 3 09:23:29 2026 -0800 Code review edits, refs #37054 diff --git src/hg/makeDb/trackDb/recount3.html src/hg/makeDb/trackDb/recount3.html index 312fd8b03af..acf9f49271c 100644 --- src/hg/makeDb/trackDb/recount3.html +++ src/hg/makeDb/trackDb/recount3.html @@ -1,116 +1,115 @@ <h2>Description</h2> <p> Recount3 is a comprehensive resource for re-analyzing RNA-seq data. It provides uniformly processed RNA-seq data and associated metadata from a wide range of studies, enabling researchers to access and analyze gene expression data in a consistent manner. Recount3 aggregates data from multiple sources, including the <a href="https://www.ncbi.nlm.nih.gov/sra/docs/" target=_blank>Sequence Read Archive (SRA)</a> and the <a href="https://commonfund.nih.gov/GTEx" target=_blank>Genotype-Tissue Expression (GTEx) project</a>, and reprocesses it using a standardized pipeline. This allows for cross-study comparisons and meta-analyses, facilitating discoveries in genomics and transcriptomics. Processed recount3 data were integrated into the <a href="https://snaptron.cs.jhu.edu/data.html" target=_blank>Snaptron system</a> for indexing and querying data summaries. Recount3 is available at: <a href="http://rna.recount.bio">http://rna.recount.bio</a>. </p> <p> These tracks display the recount3 intron data, including split read counts and splice junction motifs. </p> <h2>Display Conventions</h2> <p> Intron items are colored based on splice junction motifs and read support. Darker colors indicate higher read coverage. Split read counts and splice motifs are shown on mouseover. By default, only introns with a minimum read count of 10,000 are shown. This threshold can be changed on the track configuration page. </p> <p> The intron items are color-coded (darker colors indicate higher coverage): </p> <ul> <li><b><font color="#00bfff">Sky blue</font></b>: GT donors and AG acceptors (CT and AC on the minus strand)</li> <li><b><font color="#00ced1">Turquoise</font></b>: GC donors (GT on the minus strand)</li> <li><b><font color="#ff8c00">Orange</font></b>: AT donors and AC acceptors (GT and GT on the minus strand)</li> <li><b><font color="#a9a9a9">Grey</font></b>: Non-canonical junction motifs. These could be sequencing errors, polymorphisms, or very rare U12 introns.</li> </ul> <p> Introns can be filtered by: </p> <ul> <li><b>Intron size</b> - Length of the intron. The default range is 30 to 100,000 bases.</li> <li><b>Split read count</b> - Number of split reads supporting the intron. The default is a minimum of 10,000 reads.</li> <li><b>Splice junction motif</b> - The motif is specified in the form <em>GT/AG</em>, with canonical motifs in uppercase and unknown motifs in lowercase. The default is no filtering.</li> <li><b>Strand</b> - Filter by positive strand ('+'), negative strand ('-'), and/or unknown strand ('.'). The default is no strand filtering ('all'). </li> </ul> -</p> <h2>Methods</h2> <p> A distributed processing system for RNA-seq data called Monorail was developed. Using Monorail, recount3 processed and summarized 316,443 human and 416,803 mouse RNA-seq run accessions collected from the Sequence Read Archive (SRA), with the human runs including large-scale consortia such as GTEx v8 and The Cancer Genome Atlas (TCGA). </p> <p> Junction files were converted to BED format. For grayscaling total read count was log10 transformed and multiplied by 10 to get a score between 0 and 225, which can be found in the BED score field. </p> <h2>Data Access</h2> <p> The raw data can be explored interactively with the <a href="https://genome.ucsc.edu/cgi-bin/hgTables">Table Browser</a> or the <a href="https://genome.ucsc.edu/cgi-bin/hgIntegrator">Data Integrator</a>. For automated analysis, the data may be queried from our <a href="https://genome.ucsc.edu/goldenPath/help/api.html">REST API</a>.</p> <p> Please refer to our <a href="https://groups.google.com/a/soe.ucsc.edu/forum/#!forum/genome">mailing list archives</a> for questions or our <a href="https://genome.ucsc.edu/FAQ/FAQdownloads.html#downloads36">Data Access FAQ</a> for more information. </p> <p> The original junction files for human can be found at: </p> <ul> <li> <a href="https://snaptron.cs.jhu.edu/data/gtexv2/junctions.bgz" target="_blank"> https://snaptron.cs.jhu.edu/data/gtexv2/junctions.bgz</a> <li> <a href="https://snaptron.cs.jhu.edu/data/tcgav2/junctions.bgz" target="_blank"> https://snaptron.cs.jhu.edu/data/tcgav2/junctions.bgz</a> <li> <a href="https://snaptron.cs.jhu.edu/data/srav3h/junctions.bgz" target="_blank"> https://snaptron.cs.jhu.edu/data/srav3h/junctions.bgz</a> <li> <a href="https://snaptron.cs.jhu.edu/data/ccle/junctions.bgz" target="_blank"> https://snaptron.cs.jhu.edu/data/ccle/junctions.bgz</a> </ul> <p> The mouse junction file is available at: </p> <ul> <li> <a href="https://snaptron.cs.jhu.edu/data/srav1m/junctions.bgz" target="_blank"> https://snaptron.cs.jhu.edu/data/srav1m/junctions.bgz</a> </ul> <h2>References</h2> <p> Wilks C, Zheng SC, Chen FY, Charles R, Solomon B, Ling JP, Imada EL, Zhang D, Joseph L, Leek JT <em>et al</em>. <a href="https://genomebiology.biomedcentral.com/articles/10.1186/s13059-021-02533-6" target="_blank"> recount3: summaries and queries for large-scale RNA-seq expression and splicing</a>. <em>Genome Biol</em>. 2021 Nov 29;22(1):323. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/34844637" target="_blank">34844637</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8628444/" target="_blank">PMC8628444</a> </p>