c09a7a320420ebbd4262d6611b244a07b009336b
max
  Thu May 5 08:54:17 2022 -0700
starting docs for HMC and Jarvis, refs #29153 and refs #29154

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+<h2>Description</h2>
+
+<p>
+This container track includes various subtracks showing the results of
+constraint prediction algorithms that try to find regions of negative
+selection, where variations likely have functional impact. These algorithms do
+not use multi-species alignments to derive constraint, but use primarily human
+variation, usually from variants collected by gnomAD (see the gnomAD V2 or V3
+tracks on hg19 and hg38)
+or TOPMED (contained in our dbSNP tracks and available as a filter).
+
+The algorithms covered here are:
+<ol>
+    <li><b><a href="https://www.cardiodb.org/hmc/" target="_blank">
+    HMC - Homologous Missense Constraint</a></b>: For all possible missense
+    substitutions in PFAM domains, the number of substitutions directly
+    observed in gnomAD was counted and compared to the expected value under a
+    neutral evolution model. Homologous Residue Constraint is defined as the
+    upper limit of a 95% confidence interval for the Observed/Expected ratio.
+
+    <li><b><a href="https://github.com/astrazeneca-cgr-publications/jarvis" target="_blank">
+    JARVIS - "Junk" Annotation genome-wide Residual Variation Intolerance Score</a></b>: 
+    First scan the entire genome with a
+    sliding-window approach (using a 1-nucleotide step), recording the number of
+    all TOPMED variants and common variants, irrespective of their predicted effect,
+    within each window, to eventually calculate a single-nucleotide resolution
+    genome-wide residual variation intolerance score (gwRVIS). Then combine
+    gwRVIS, primary genomic sequence context, and additional genomic
+    annotations with a multi-module deep learning framework to infer
+    pathogenicity of noncoding regions that still remains naïve to existing
+    phylogenetic conservation metrics
+
+</ol>
+
+
+<h2>Display Conventions and Configuration</h2>
+
+<h2>Methods</h2>
+
+<p>
+<b>HMC:</b> 
+</p>
+
+<h2>Credits</h2>
+
+<p>
+Thanks to Jean-Madeleine Desainteagathe (APHP Paris, France) for suggesting the HMC track and to Xialei Zhang for providing the HMC data file.
+</p>
+
+<h2>References</h2>
+
+<p>
+Xiaolei Zhang, Pantazis I. Theotokis, Nicholas Li, the SHaRe Investigators, Caroline F. Wright, Kaitlin E. Samocha, Nicola Whiffin, James S. Ware
+<a href="https://doi.org/10.1101/2022.02.16.22271023" target="_blank">
+Genetic constraint at single amino acid resolution improves missense variant prioritisation and gene discovery</a>.
+<em>Medrxiv</em> 2022.02.16.22271023
+</p>