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/hg19/abSplice.html src/hg/makeDb/trackDb/human/hg19/abSplice.html deleted file mode 100644 index 3bf5db4..0000000 --- src/hg/makeDb/trackDb/human/hg19/abSplice.html +++ /dev/null @@ -1,76 +0,0 @@ -<h2>Description</h2> -<p> -</p> -<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/">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. - -<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> -</ul> -Scores below 0.01 are not displayed -</p> -<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 48 GTEX tissues. -</p> - -<h2>Data Access</h2> -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>. <br> -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>AbSplice scores are also available at the -<a target="_blank" href="https://zenodo.org/records/10776853/files/AbSplice_DNA_hg38_snvs_high_scores.zip?download=1">public repository</a> -created by the authors. - -<h2>Methods</h2> -<p> -Data was converted from the file -(<a href="https://zenodo.org/records/10776853/files/AbSplice_DNA_hg19_snvs_high_scores.zip" -target="_blank">AbSplice_DNA_hg19_snvs_high_scores.zip</a>) provided by the authors at -<a href="https://zenodo.org/records/7871809" 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 -<a a target="_blank" href="https://github.com/ucscGenomeBrowser/kent/tree/master/src/hg/makeDb/outside/abSplice/AbSplice.hg19.makedoc"> -custom Python script</a>. -</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>