{"id":1506,"date":"2020-08-01T13:47:50","date_gmt":"2020-08-01T13:47:50","guid":{"rendered":"https:\/\/blogs.bmj.com\/jmg\/?p=1506"},"modified":"2026-02-23T23:52:32","modified_gmt":"2026-02-23T23:52:32","slug":"data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy","status":"publish","type":"post","link":"https:\/\/blogs.bmj.com\/jmg\/2020\/08\/01\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\/","title":{"rendered":"Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy (Contributed by Adam Waring)"},"content":{"rendered":"

In Mendelian disease genes, missense-variants may cluster in specific functional regions of the protein. Often, there is a complimentary depletion in controls due to population-level constraint. We developed two statistical methods to interrogate this signal, one for gene-association, another for variant interpretation. For gene-discovery efforts, we demonstrate how modeling clustering can improve power. For variant interpretation, we show how parsimonious generalized-additive models are capable of estimating regional burden throughout a linear protein sequence, highlighting mutational hotspots. This proved informative when applied to core hypertrophic cardiomyopathy causing genes with extension to integrate pathogenicity prediction scores. An associated R package and web application facilitates the usage of these methods. (https:\/\/jmg.bmj.com\/content\/early\/2020\/07\/30\/jmedgenet-2020-106922<\/a> )<\/p>\n

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In Mendelian disease genes, missense-variants may cluster in specific functional regions of the protein. Often, there is a complimentary depletion in controls due to population-level constraint. We developed two statistical methods to interrogate this signal, one for gene-association, another for variant interpretation. For gene-discovery efforts, we demonstrate how modeling clustering can improve power. For variant […]<\/p>\n

Read More…<\/a><\/p>\n","protected":false},"author":123,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-1506","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"\nData-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy (Contributed by Adam Waring) - JMG Contact blog<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blogs.bmj.com\/jmg\/2020\/08\/01\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy (Contributed by Adam Waring) - JMG Contact blog\" \/>\n<meta property=\"og:description\" content=\"In Mendelian disease genes, missense-variants may cluster in specific functional regions of the protein. Often, there is a complimentary depletion in controls due to population-level constraint. We developed two statistical methods to interrogate this signal, one for gene-association, another for variant interpretation. For gene-discovery efforts, we demonstrate how modeling clustering can improve power. For variant [...]Read More...\" \/>\n<meta property=\"og:url\" content=\"https:\/\/blogs.bmj.com\/jmg\/2020\/08\/01\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\/\" \/>\n<meta property=\"og:site_name\" content=\"JMG Contact blog\" \/>\n<meta property=\"article:published_time\" content=\"2020-08-01T13:47:50+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2026-02-23T23:52:32+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/blogs.bmj.com\/jmg\/files\/2020\/08\/Figure3_hotspot_plus_models.png\" \/>\n\t<meta property=\"og:image:width\" content=\"7680\" \/>\n\t<meta property=\"og:image:height\" content=\"3840\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"hqqu\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" content=\"@HuiQiQu\" \/>\n<meta name=\"twitter:label1\" content=\"Written by\" \/>\n\t<meta name=\"twitter:data1\" content=\"hqqu\" \/>\n\t<meta name=\"twitter:label2\" content=\"Est. reading time\" \/>\n\t<meta name=\"twitter:data2\" content=\"1 minute\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\\\/\\\/schema.org\",\"@graph\":[{\"@type\":\"Article\",\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/#article\",\"isPartOf\":{\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/\"},\"author\":{\"name\":\"hqqu\",\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/#\\\/schema\\\/person\\\/be0250f8d5b52412c3e7c222dabd591b\"},\"headline\":\"Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy (Contributed by Adam Waring)\",\"datePublished\":\"2020-08-01T13:47:50+00:00\",\"dateModified\":\"2026-02-23T23:52:32+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/\"},\"wordCount\":131,\"commentCount\":0,\"publisher\":{\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/#organization\"},\"image\":{\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/#primaryimage\"},\"thumbnailUrl\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/files\\\/2020\\\/08\\\/Figure3_hotspot_plus_models-300x150.png\",\"inLanguage\":\"en-US\",\"potentialAction\":[{\"@type\":\"CommentAction\",\"name\":\"Comment\",\"target\":[\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/#respond\"]}]},{\"@type\":\"WebPage\",\"@id\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/\",\"url\":\"https:\\\/\\\/blogs.bmj.com\\\/jmg\\\/2020\\\/08\\\/01\\\/data-driven-modelling-of-mutational-hotspots-and-in-silico-predictors-in-hypertrophic-cardiomyopathy\\\/\",\"name\":\"Data-driven modelling of mutational hotspots and in silico predictors in hypertrophic cardiomyopathy (Contributed by Adam Waring) - 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