092b1f6d8b05019906c903090236b8d7a3a59220 lrnassar Wed May 29 16:04:16 2024 -0700 Addin the desc page for the spliceAI track, refs #27141 diff --git src/hg/makeDb/trackDb/human/spliceAI.html src/hg/makeDb/trackDb/human/spliceAI.html new file mode 100644 index 0000000..05fdbd6 --- /dev/null +++ src/hg/makeDb/trackDb/human/spliceAI.html @@ -0,0 +1,77 @@ +<!DOCTYPE html> +<html> +<head> +</head> + +<body> +<h2>Description</h2> +<p> +SpliceAI is an <a href="https://github.com/Illumina/SpliceAI" target="_blank">open-source</a> deep +learning splicing prediction algorithm that can predict splicing alterations caused by DNA variations. +Such variants may activate nearby cryptic splice sites, leading to abnormal transcript isoforms. +SpliceAI was developed at Illumina; a +<a href="https://spliceailookup.broadinstitute.org" target="_blank">lookup tool</a> +is provided by the Broad institute. +</p> + +<h2>Display Conventions</h2> +<p> +Variants are colored by their predicted effects: +<ul> +<li><b><font color="#FF0000">Acceptor gain (red)</font></b> </li> +<li><b><font color="#FF8000">Acceptor loss (orange)</font></b> </li> +<li><b><font color="#0000FF">Donor gain (blue)</font></b> </li> +<li><b><font color="#D400FF">Donor loss (violet)</font></b> </li> +</ul> +Mouseover on items shows the variant, gene name, type of change (donor gain/loss, acceptor gain/loss), +location of affected cryptic splice, and spliceAI score. Clicking on any item brings up a table with this +information. +</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> +SpliceAI scores for hg38 were obtained in VCF format from +<a href="https://ftp.ensembl.org/pub/data_files/homo_sapiens/GRCh38/variation_plugins" target="_blank">the Ensembl ftp site</a>. +</p> + +<h2>Methods</h2> +<p> +The spliceAI scores are represented in the VCF INFO field as +<code style="background-color: lightgray;">SpliceAI=G|OR4F5|0.01|0.00|0.00|0.00|-32|49|-40|-31</code> <br> +Here, the pipe-separated fields contain +<ul> +<li>ALT allele</li> +<li>Gene name</li> +<li>Acceptor gain score</li> +<li>Acceptor loss score</li> +<li>Donor gain score</li> +<li>Donor loss score</li> +<li>Relative location of affected cryptic acceptor</li> +<li>Relative location of affected acceptor</li> +<li>Relative location of affected cryptic donor</li> +<li>Relative location of affected donor</li> +</ul> +To create the track we selected only those variants with a score equal to or greater than 0.02. +</p> + +<h2>References</h2> +<p> +Jaganathan K, Kyriazopoulou Panagiotopoulou S, McRae JF, Darbandi SF, Knowles D, Li YI, Kosmicki JA, +Arbelaez J, Cui W, Schwartz GB <em>et al</em>. +<a href="https://linkinghub.elsevier.com/retrieve/pii/S0092-8674(18)31629-5" target="_blank"> +Predicting Splicing from Primary Sequence with Deep Learning</a>. +<em>Cell</em>. 2019 Jan 24;176(3):535-548.e24. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/30661751" target="_blank">30661751</a> +</p> +</body> +</html>