f763b6b740aa6f6032b803d3eab5ac2c3e554a4e max Tue Jun 17 08:46:54 2025 -0700 fixing up revel docs after email from Heidi Rehm, no redmine. diff --git src/hg/makeDb/trackDb/human/revel.html src/hg/makeDb/trackDb/human/revel.html index 095ab2f787b..b1f5e14851b 100644 --- src/hg/makeDb/trackDb/human/revel.html +++ src/hg/makeDb/trackDb/human/revel.html @@ -1,24 +1,24 @@ <h2>Description</h2> <p> This track collection shows <a href="https://sites.google.com/site/revelgenomics/" -target="_blank">Rare Exome Variant Ensemble Learner</a> (REVEL) scores for predicting -the deleteriousness of each nucleotide change in the genome. +target="_blank">Rare Exome Variant Ensemble Learner</a> (REVEL) scores that can be +used as evidence for pathogenicity annotations. </p> <p> -REVEL is an ensemble method for predicting the pathogenicity of missense variants +REVEL is an ensemble method for predicting a score for missense variants based on a combination of scores from 13 individual tools: MutPred, FATHMM v2.3, VEST 3.0, PolyPhen-2, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP++, SiPhy, phyloP, and phastCons. REVEL was trained using recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. The REVEL score for an individual missense variant can range from 0 to 1, with higher scores reflecting greater likelihood that the variant is disease-causing. </p> <p>Most authors of deleteriousness scores argue against using fixed cutoffs in diagnostics. But to give an idea of the meaning of the score value, the REVEL authors note: "For example, 75.4% of disease mutations but only 10.9% of neutral variants (and 12.4% of all ESVs) have a REVEL score above 0.5, corresponding to a sensitivity of 0.754 and specificity of 0.891. Selecting a more stringent REVEL score threshold of 0.75 would result in higher specificity @@ -73,55 +73,60 @@ field, some transcripts have been agreed-on as more relevant for a disease, e.g. because only certain transcripts may be expressed in the relevant tissue. So the choice of the most relevant transcript, and as such the REVEL score, may be a question of manual curation standards rather than a result of the variant itself. </p> </ul> <p> When using this track, zoom in until you can see every basepair at the top of the display. Otherwise, there are several nucleotides per pixel under your mouse cursor and no score will be shown on the mouseover tooltip. </p> <p><b>Track colors</b></p> <p> -This track is colored according to <a target="_blank" href="https://www.sciencedirect.com/science/article/pii/S000292972200461X">Table 2 in Vikas et al</a>. The colors represent the recommended ACMG/AMP score cutoffs. +This track is colored according to <a target="_blank" href="https://www.sciencedirect.com/science/article/pii/S000292972200461X">Table 2 in Pejaver et al</a>. The colors represent the recommended ACMG/AMP score cutoffs. <table style="text-align: left;"> <thead> <tr> <th>Range</th> <th>Classification</th> </tr> </thead> <tbody> <tr> <td>≥ .644</td> - <td style="color: rgb(255,0,0);">Pathogenic</td> + <td style="color: rgb(255,0,0);">Pathogenic_supporting</td> </tr> <tr> <td>.643 - .291</td> <td style="color: rgb(192,192,192);">Neutral</td> </tr> <tr> <td>≤ .290</td> - <td style="color: rgb(80,166,230);">Benign</td> + <td style="color: rgb(80,166,230);">Benign_supporting</td> </tr> </tbody> </table> +<p> +More details on these scoring ranges can be found in Bergquist et al Genet Med 2025, Table 2: +<img src="../images/bergquist25.png" alt="Table 2 from Bergquist Genet Med 2025"> +</p> + <p>For hg38, note that the data was converted from the hg19 data using the UCSC liftOver program, by the REVEL authors. This can lead to missing values or duplicated values. When a hg38 position is annotated with two scores due to the lifting, the authors removed all the scores for this position. They did the same when the reference allele has changed from hg19 to hg38. Also, on hg38, the track has the "lifted" icon to indicate this. You can double-check if a nucleotide position is possibly affected by the lifting procedure by activating the track "Hg19 Mapping" under "Mapping and Sequencing". </p> <h2>Data access</h2> <p> REVEL scores are available at the <a href="https://sites.google.com/site/revelgenomics/" target="_blank"> @@ -149,34 +154,45 @@ <a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">here</a>. The tools can also be used to obtain features confined to given range, e.g. <br> <br> <tt>bigWigToBedGraph -chrom=chr1 -start=100000 -end=100500 http://hgdownload.soe.ucsc.edu/gbdb/$db/revel/a.bw stdout</tt> <br> <h2>Methods</h2> <p> Data were converted from the files provided on <a href="https://sites.google.com/site/revelgenomics/downloads?authuser=0" target = "_blank">the REVEL Downloads website</a>. As with all other tracks, a full log of all commands used for the conversion is available in our <a target=_blank href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/">source repository</a>, for <a target=_blank href="https://raw.githubusercontent.com/ucscGenomeBrowser/kent/master/src/hg/makeDb/doc/hg19.txt">hg19</a> and <a target=_blank href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg38/revel.txt">hg38</a>. The release used for each assembly is shown on the track description page. - </p> <h2>Credits</h2> <p> Thanks to the REVEL development team for providing precomputed data and fixing duplicated values in the hg38 files. </p> <h2>References</h2> <p> Ioannidis NM, Rothstein JH, Pejaver V, Middha S, McDonnell SK, Baheti S, Musolf A, Li Q, Holzinger E, Karyadi D, et al. <a href="https://doi.org/10.1016/j.ajhg.2016.08.016" target = _blank"> REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants</a> <em>Am J Hum Genet</em>. 2016 Oct 6;99(4):877-885. PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/27666373" target="_blank">27666373</a>; PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5065685/" target="_blank">PMC5065685</a> </p> + + +<p> +Bergquist T, Stenton SL, Nadeau EAW, Byrne AB, Greenblatt MS, Harrison SM, Tavtigian SV, +O'Donnell-Luria A, Biesecker LG, Radivojac P <em>et al</em>. +<a href="https://linkinghub.elsevier.com/retrieve/pii/S1098-3600(25)00049-8" target="_blank"> +Calibration of additional computational tools expands ClinGen recommendation options for variant +classification with PP3/BP4 criteria</a>. +<em>Genet Med</em>. 2025 Mar 10;27(6):101402. +PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/40084623" target="_blank">40084623</a> +</p> +