8c2f7318d8d821de9b2a25750586a94ab5e8c1bb lrnassar Fri Nov 15 18:50:19 2024 -0800 Giving the UI link cronjob some love by fixing all the 301 redirects. These are the bulk of the items listed on the cron. No RM. diff --git src/hg/makeDb/trackDb/human/constraintSuper.html src/hg/makeDb/trackDb/human/constraintSuper.html index 6c7688b..52ba63f 100644 --- src/hg/makeDb/trackDb/human/constraintSuper.html +++ src/hg/makeDb/trackDb/human/constraintSuper.html @@ -42,31 +42,31 @@ and compared to the expected value under a neutral evolution model (Expected). The upper limit of a 95% confidence interval for the Observed/Expected ratio is defined as the HMC score. Missense variants disrupting the amino-acid positions with HMC<0.8 are predicted to be likely deleterious. This score only covers PFAM domains within coding regions. <li><b><a href="https://stuart.radboudumc.nl/metadome/" target="_blank"> MetaDome - Tolerance Landscape Score</a> (hg19 only)</b>: MetaDome Tolerance Landscape scores are computed as a missense over synonymous variant count ratio, which is calculated in a sliding window (with a size of 21 codons/residues) to provide a per-position indication of regional tolerance to missense variation. The variant database was gnomAD and the score corrected for codon composition. Scores <0.7 are considered intolerant. This score covers only coding regions. - <li><b><a href="http://biosig.unimelb.edu.au/mtr-viewer/" target="_blank"> + <li><b><a href="https://biosig.lab.uq.edu.au/mtr-viewer/" target="_blank"> MTR - Missense Tolerance Ratio</a> (hg19 only)</b>: Missense Tolerance Ratio (MTR) scores aim to quantify the amount of purifying selection acting specifically on missense variants in a given window of protein-coding sequence. It is estimated across sliding windows of 31 codons (default) and uses observed standing variation data from the WES component of gnomAD / the Exome Aggregation Consortium Database (ExAC), version 2.0. Scores were computed using Ensembl v95 release. The number of gnomAD 2 exomes used here is higher than the number of gnomAD 3 samples (125 exoms versus 76k full genomes), but this score only covers coding regions. <li><b><a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9329122/" target="_blank"> UK Biobank depletion rank score</a> (hg38 only)</b>: Halldorsson et al. tabulated the number of UK Biobank variants in each 500bp window of the genome and compared this number to an expected number given the heptamer nucleotide composition of the window and the fraction of @@ -157,31 +157,31 @@ <h3>MTR</h3> <p> MTR data can be found on two tracks, <b>MTR All data</b> and <b>MTR Scores</b>. In the <b>MTR Scores</b> track the data has been converted into 4 separate signal tracks representing each base pair mutation, with the lowest possible score shown when multiple transcripts overlap at a position. Overlaps can happen since this score is derived from transcripts and multiple transcripts can overlap. A horizontal line is drawn on the 0.8 score line to roughly represent the 25th percentile, meaning the items below may be of particular interest. It is recommended that the data be explored using this version of the track, as it condenses the information substantially while retaining the magnitude of the data.</p> <p>Any specific point mutations of interest can then be researched in the <b> MTR All data</b> track. This track contains all of the information from -<a href="http://biosig.unimelb.edu.au/mtr-viewer/downloads" target="_blank"> +<a href="https://biosig.lab.uq.edu.au/mtr-viewer/downloads" target="_blank"> MTRV2</a> including more than 3 possible scores per base when transcripts overlap. A mouse-over on this track shows the ref and alt allele, as well as the MTR score and the MTR score percentile. Filters are available for MTR score, False Discovery Rate (FDR), MTR percentile, and variant consequence. By default, only items in the bottom 25 percentile are shown. Items in the track are colored according to their MTR percentile:</p> <ul> <li><b><font color=green>Green items</font></b> MTR percentiles over 75 <li><b><font color=black>Black items</font></b> MTR percentiles between 25 and 75 <li><b><font color=red>Red items</font></b> MTR percentiles below 25 <li><b><font color=blue>Blue items</font></b> No MTR score </ul> <p> <b>Interpretation:</b> Regions with low MTR scores were seen to be enriched with pathogenic variants. For example, ClinVar pathogenic variants were seen to @@ -217,31 +217,31 @@ This file was parsed with a python script to create the two tracks. For the first track the scores were aggregated for each coordinate, then the lowest score chosen for any overlaps and the result written out to bedGraph format. The file was then converted to bigWig with the <code>bedGraphToBigWig</code> utility. For the second track the file was reorganized into a bed 4+3 and conveted to bigBed with the <code>bedToBigBed</code> utility.</p> <p> See the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg/makeDb/doc/hg19.txt" target=_blank>hg19 makeDoc</a> for details including the build script.</p> <p> The raw MetaDome data can also be accessed via their <a target="_blank" href="https://zenodo.org/record/6625251">Zenodo handle</a>.</p> <h3>MTR</h3> <p> -<a href="http://biosig.unimelb.edu.au/mtr-viewer/downloads" target="_blank">V2 +<a href="https://biosig.lab.uq.edu.au/mtr-viewer/downloads" target="_blank">V2 file</a> was downloaded and columns were reshuffled as well as itemRgb added for the <b>MTR All data</b> track. For the <b>MTR Scores</b> track the file was parsed with a python script to pull out the highest possible MTR score for each of the 3 possible mutations at each base pair and 4 tracks built out of these values representing each mutation.</p> <p> See the <a href="https://github.com/ucscGenomeBrowser/kent/blob/master/src/hg /makeDb/doc/hg19.txt" target=_blank>hg19 makeDoc</a> entry on MTR for more info.</p> <h2>Data Access</h2> <p> The raw data can be explored interactively with the <a href="../hgTables">Table Browser</a>, or the <a href="../hgIntegrator">Data Integrator</a>. For automated access, this track, like all others, is available via our <a href="../goldenPath/help/api.html">API</a>. However, for bulk processing, it is recommended to download the dataset. </p>