72924c5113cc9889caa9ec788cb1fff7ddcee17f lrnassar Mon Jun 17 16:37:50 2024 -0700 Staging updated/new SpliceAI data which is now QA Ready. Refs #27141 diff --git src/hg/makeDb/trackDb/human/spliceAI.html src/hg/makeDb/trackDb/human/spliceAI.html index 05fdbd6..c45f756 100644 --- src/hg/makeDb/trackDb/human/spliceAI.html +++ src/hg/makeDb/trackDb/human/spliceAI.html @@ -1,77 +1,92 @@
SpliceAI is an open-source 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
lookup tool
-is provided by the Broad institute.
+is provided by the Broad institute.
+Important: The SpliceAI data on the UCSC Genome Browser is directly from
+Illumina (See Data Access below). However, since SpliceAI refers to the algorithm, and not the computed dataset,
+the data on the BROAD server or other sources may have some differences between them.
Variants are colored by their predicted effects:
+The scores range from 0 to 1 and can be interpreted as the +probability of the variant being splice-altering. In the paper, a detailed characterization is +provided for 0.2 (high recall), 0.5 (recommended), and 0.8 (high precision) cutoffs.
-SpliceAI scores for hg38 were obtained in VCF format from -the Ensembl ftp site. +FOR ACADEMIC AND NOT-FOR-PROFIT RESEARCH USE ONLY. The SpliceAI scores are +made available by Illumina only for academic or not-for-profit research only. +By accessing the SpliceAI data, you acknowledge and agree that you may only +use this data for your own personal academic or not-for-profit research only, +and not for any other purposes. You may not use this data for any for-profit, +clinical, or other commercial purpose without obtaining a commercial license +from Illumina, Inc.
+The data were downloaded from Illumina.
The spliceAI scores are represented in the VCF INFO field as
-SpliceAI=G|OR4F5|0.01|0.00|0.00|0.00|-32|49|-40|-31
+SpliceAI=G|OR4F5|0.01|0.00|0.00|0.00|-32|49|-40|-31
Here, the pipe-separated fields contain
Jaganathan K, Kyriazopoulou Panagiotopoulou S, McRae JF, Darbandi SF, Knowles D, Li YI, Kosmicki JA, Arbelaez J, Cui W, Schwartz GB et al. Predicting Splicing from Primary Sequence with Deep Learning. Cell. 2019 Jan 24;176(3):535-548.e24. PMID: 30661751