d4262bca1e7f48775cd45562ff7e8a77dae739b1 gperez2 Wed Apr 24 11:41:11 2024 -0700 Combining the two abSplice.ra and html files for hg38 and hg19, refs #33251 diff --git src/hg/makeDb/trackDb/human/abSplice.html src/hg/makeDb/trackDb/human/abSplice.html new file mode 100644 index 0000000..f053031 --- /dev/null +++ src/hg/makeDb/trackDb/human/abSplice.html @@ -0,0 +1,75 @@ +<h2>Description</h2> +<p> +AbSplice is a method that predicts aberrant splicing across human tissues, as described in Wagner, +Çelik et al., 2023. This track displays precomputed AbSplice scores for all possible +single-nucleotide variants genome-wide. The scores represent the probability that a given variant +causes aberrant splicing in a given tissue. +<a target="_blank" href="https://github.com/gagneurlab/absplice/tree/master">AbSplice</a> scores +can be computed from VCF files and are based on quantitative tissue-specific splice site annotations +(<a target="_blank" href="https://github.com/gagneurlab/splicemap">SpliceMaps</a>). +While SpliceMaps can be generated for any tissue of interest from a cohort of RNA-seq samples, this +track includes 49 tissues available from the +<a target="_blank" href="https://www.gtexportal.org/home/samplingSitePage">Genotype-Tissue +Expression (GTEx) dataset</a>. +</p> + +<h2>Display Conventions</h2> +<p> +The AbSplice score is a probability estimate of how likely aberrant splicing of some sort takes +place in a given tissue. The authors <a target="_blank" href="https://github.com/gagneurlab/absplice?tab=readme-ov-file#output" +>suggest</a> three cutoffs which are represented by color in the track. +</p> + +<ul> +<li><b><font color="#FF0000">High (red)</font></b> - <b> + An AbSplice score over 0.2</b> indicates a high likelihood of aberrant splicing in at least one tissue.</li> +<li><b><font color="#FF8000">Medium (orange)</font></b> - <b> + A score between 0.05 and 0.2 </b> indicates a medium likelihood.</li> +<li><b><font color="#0000FF">Low (blue)</font></b> - <b> + A score between 0.01 and 0.05 </b> indicates a low likelihood.</li> +<li><b>Scores below 0.01 are not displayed.</b></li> +</ul> +<p> +Mouseover on items shows the gene name, maximum score, and tissues that had this score. Clicking on +any item brings up a table with scores for all 49 GTEX tissues. +</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>. +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>Precomputed AbSplice-DNA scores in all 49 GTEx tissues are available at +<a target="_blank" href="https://zenodo.org/search?q=AbSplice-DNA&l=list&p=1&s=10&sort=bestmatch"> +Zenodo</a>. + +<h2>Methods</h2> +<p> +Data was converted from the files (AbSplice_DNA_ $db _snvs_high_scores.zip) provided by the authors +at <a href="https://zenodo.org/search?q=AbSplice-DNA&l=list&p=1&s=10&sort=bestmatch" +target="_blank">zenodo.org</a>. Files in the +score_cutoff=0.01 directory were concatenated. To convert the data to bigBed format, scores and +their tissues were selected from the AbSplice_DNA fields and maximum scores, and then calculated +using a custom Python script, which can be found in the +<a a target="_blank" href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/outside/abSplice/"> +makeDoc</a> from our GitHub repository.</p> + +<h2>Credits</h2> +<p> +Thanks to Nils Wagner for helpful comments and suggestions.</p> + +<h2>References</h2> +<p> +Wagner N, Çelik MH, Hölzlwimmer FR, Mertes C, Prokisch H, Yépez VA, Gagneur J. +<a href="https://doi.org/10.1038/s41588-023-01373-3" target="_blank"> +Aberrant splicing prediction across human tissues</a>. +<em>Nat Genet</em>. 2023 May;55(5):861-870. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/37142848" target="_blank">37142848</a> +</p>