<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Computational Genomics | Tanigawa Lab</title><link>https://tanigawalab.org/tags/computational-genomics/</link><atom:link href="https://tanigawalab.org/tags/computational-genomics/index.xml" rel="self" type="application/rss+xml"/><description>Computational Genomics</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en</language><lastBuildDate>Tue, 01 Jul 2025 00:00:00 +0000</lastBuildDate><image><url>https://tanigawalab.org/media/logo_hu_6ec5cb994dd998e6.png</url><title>Computational Genomics</title><link>https://tanigawalab.org/tags/computational-genomics/</link></image><item><title>Disease heterogeneity dissection</title><link>https://tanigawalab.org/research/disease-heterogeneity/</link><pubDate>Tue, 01 Jul 2025 00:00:00 +0000</pubDate><guid>https://tanigawalab.org/research/disease-heterogeneity/</guid><description>&lt;p&gt;Diagnosis for the same disease affects individuals differently. However, we don’t know how best to represent biologically meaningful axes of variation within a disease, beyond the standard case vs. control comparison or proxy measure of severity. We combine human genetics, causal inference, and modern AI to address this challenge.&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Decomposition of genetic associations across many phenotypes&lt;/li&gt;
&lt;li&gt;Causal representation learning from pleiotropic associations&lt;/li&gt;
&lt;li&gt;Assessing the biological bases of disease subtypes&lt;/li&gt;
&lt;/ul&gt;
&lt;h2 id="representative-studies"&gt;Representative studies&lt;/h2&gt;
&lt;div class="not-prose research-publication-cards"&gt;
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&lt;div class="relative overflow-hidden aspect-[16/9] bg-gradient-to-br from-zinc-100 to-zinc-200 dark:from-zinc-800 dark:to-zinc-900"&gt;
&lt;a href="https://tanigawalab.org/publications/2019/degas/" class="block"&gt;
&lt;img class="w-full h-full transition-transform duration-500 ease-out group-hover:scale-105 object-fill"
srcset="https://tanigawalab.org/publications/2019/degas/featured_hu_298ed8f352d934f3.webp 400w, https://tanigawalab.org/publications/2019/degas/featured_hu_88e32a69be907a6f.webp 600w, https://tanigawalab.org/publications/2019/degas/featured_hu_a1582a459169185b.webp 800w, https://tanigawalab.org/publications/2019/degas/featured_hu_e1affe50ddf0acd2.webp 800w"
sizes="(max-width: 768px) 100vw, (max-width: 1200px) 50vw, 33vw"
src="https://tanigawalab.org/publications/2019/degas/featured_hu_298ed8f352d934f3.webp"
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alt="Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology featured image"&gt;
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&lt;div class="flex flex-wrap gap-2"&gt;
&lt;a href="https://tanigawalab.org/tags/uk-biobank/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
UK Biobank
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&lt;/a&gt;
&lt;a href="https://tanigawalab.org/tags/latent-components/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Latent Components
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&lt;/a&gt;
&lt;a href="https://tanigawalab.org/tags/obesity/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Obesity
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+1 more
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&lt;h3 id="card-title-a650e4193e33852896b21ba917b05324" class="text-xl font-bold tracking-tight text-zinc-900 dark:text-zinc-100 group-hover:text-blue-600 dark:group-hover:text-blue-400 transition-colors duration-200 leading-tight"&gt;
&lt;a href="https://tanigawalab.org/publications/2019/degas/" class="hover:underline"&gt;
Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology
&lt;/a&gt;
&lt;/h3&gt;
&lt;p class="text-zinc-600 dark:text-zinc-400 text-base leading-relaxed line-clamp-3"&gt;
We developed DeGAs to decompose shared genetic associations across 2,138 UK Biobank phenotypes and identify their underlying pleiotropic structure.
&lt;/p&gt;
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&lt;img alt="avatar" class="rounded-full object-cover" src="https://tanigawalab.org/authors/yosuke-tanigawa/avatar_hu_e4b15cd8591d702.webp" width="24" height="24" loading="lazy" decoding="async" /&gt;
&lt;/div&gt;
&lt;span class="truncate max-w-[9rem] text-sm"&gt;Yosuke Tanigawa, Ph.D.&lt;/span&gt;
&lt;/div&gt;
&lt;span class="opacity-40"&gt;•&lt;/span&gt;
&lt;time class="hidden sm:inline whitespace-nowrap" datetime="2019-12-31"&gt;
Dec 31, 2019
&lt;/time&gt;
&lt;span class="hidden sm:inline opacity-40"&gt;•&lt;/span&gt;
&lt;span class="hidden sm:inline whitespace-nowrap"&gt;1 min read&lt;/span&gt;
&lt;/div&gt;
&lt;div class="pt-2 border-t border-zinc-200/50 dark:border-zinc-700/50"&gt;
&lt;a href="https://tanigawalab.org/publications/2019/degas/" class="inline-flex items-center gap-2 text-primary-600 dark:text-primary-400 hover:text-primary-700 dark:hover:text-primary-300 font-medium text-sm transition-all duration-300 group/link"&gt;
&lt;span&gt;Read more&lt;/span&gt;
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&lt;div class="relative overflow-hidden aspect-[16/9] bg-gradient-to-br from-zinc-100 to-zinc-200 dark:from-zinc-800 dark:to-zinc-900"&gt;
&lt;a href="https://tanigawalab.org/publications/2021/dprs/" class="block"&gt;
&lt;img class="w-full h-full transition-transform duration-500 ease-out group-hover:scale-105 object-fill"
srcset="https://tanigawalab.org/publications/2021/dprs/featured_hu_cfe45e0f970bf14d.webp 400w, https://tanigawalab.org/publications/2021/dprs/featured_hu_1d8eb57d67dde97f.webp 600w, https://tanigawalab.org/publications/2021/dprs/featured_hu_5806cde0f8130698.webp 800w, https://tanigawalab.org/publications/2021/dprs/featured_hu_b900259490964ef1.webp 800w"
sizes="(max-width: 768px) 100vw, (max-width: 1200px) 50vw, 33vw"
src="https://tanigawalab.org/publications/2021/dprs/featured_hu_cfe45e0f970bf14d.webp"
width="800"
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alt="Polygenic risk modeling with latent trait-related genetic components featured image"&gt;
&lt;/a&gt;
&lt;div class="absolute inset-0 pointer-events-none bg-gradient-to-t from-black/10 via-transparent to-transparent opacity-0 group-hover:opacity-100 transition-opacity duration-300"&gt;&lt;/div&gt;
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&lt;div class="p-8 space-y-4"&gt;
&lt;div class="flex flex-wrap gap-2"&gt;
&lt;a href="https://tanigawalab.org/tags/polygenic-scores/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Polygenic Scores
&lt;/span&gt;
&lt;/a&gt;
&lt;a href="https://tanigawalab.org/tags/latent-components/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Latent Components
&lt;/span&gt;
&lt;/a&gt;
&lt;a href="https://tanigawalab.org/tags/disease-heterogeneity/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Disease Heterogeneity
&lt;/span&gt;
&lt;/a&gt;
&lt;/div&gt;
&lt;h3 id="card-title-357785520e0fce8f6507fb29f9ddc5cf" class="text-xl font-bold tracking-tight text-zinc-900 dark:text-zinc-100 group-hover:text-blue-600 dark:group-hover:text-blue-400 transition-colors duration-200 leading-tight"&gt;
&lt;a href="https://tanigawalab.org/publications/2021/dprs/" class="hover:underline"&gt;
Polygenic risk modeling with latent trait-related genetic components
&lt;/a&gt;
&lt;/h3&gt;
&lt;p class="text-zinc-600 dark:text-zinc-400 text-base leading-relaxed line-clamp-3"&gt;
Polygenic risk score (PRS) has been proposed for disease risk prediction with potential clinical relevance for some traits, but its personalized interpretation is generally …
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&lt;time class="hidden sm:inline whitespace-nowrap" datetime="2021-02-08"&gt;
Feb 8, 2021
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&lt;span class="hidden sm:inline opacity-40"&gt;•&lt;/span&gt;
&lt;span class="hidden sm:inline whitespace-nowrap"&gt;1 min read&lt;/span&gt;
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&lt;div class="pt-2 border-t border-zinc-200/50 dark:border-zinc-700/50"&gt;
&lt;a href="https://tanigawalab.org/publications/2021/dprs/" class="inline-flex items-center gap-2 text-primary-600 dark:text-primary-400 hover:text-primary-700 dark:hover:text-primary-300 font-medium text-sm transition-all duration-300 group/link"&gt;
&lt;span&gt;Read more&lt;/span&gt;
&lt;svg class="w-4 h-4 transition-transform group-hover/link:translate-x-1" fill="none" stroke="currentColor" viewBox="0 0 24 24" aria-hidden="true"&gt;
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&lt;div class="group bg-white/90 dark:bg-zinc-900/90 backdrop-blur-sm rounded-2xl ring-1 ring-zinc-900/5 dark:ring-white/10 shadow-lg overflow-hidden transition-all duration-300 ease-out hover:shadow-xl hover:shadow-blue-500/10 hover:-translate-y-2 focus-within:ring-2 focus-within:ring-blue-500/50" role="article" aria-labelledby="card-title-25754c58734bea9449eac92e150166c6"&gt;
&lt;div class="relative overflow-hidden aspect-[16/9] bg-gradient-to-br from-zinc-100 to-zinc-200 dark:from-zinc-800 dark:to-zinc-900"&gt;
&lt;a href="https://tanigawalab.org/publications/2021/degas-bbj/" class="block"&gt;
&lt;img class="w-full h-full transition-transform duration-500 ease-out group-hover:scale-105 object-fill"
srcset="https://tanigawalab.org/publications/2021/degas-bbj/featured_hu_3a1bfe30b78adaa7.webp 400w, https://tanigawalab.org/publications/2021/degas-bbj/featured_hu_62bfe907569a84e9.webp 600w, https://tanigawalab.org/publications/2021/degas-bbj/featured_hu_bc51a9d9e9559d55.webp 800w, https://tanigawalab.org/publications/2021/degas-bbj/featured_hu_55c26ebfa9be13b6.webp 800w"
sizes="(max-width: 768px) 100vw, (max-width: 1200px) 50vw, 33vw"
src="https://tanigawalab.org/publications/2021/degas-bbj/featured_hu_3a1bfe30b78adaa7.webp"
width="800"
height="450"
loading="lazy"
decoding="async"
style="position: absolute; height: 100%; width: 100%; inset: 0px; color: transparent;"
alt="A cross-population atlas of genetic associations for 220 human phenotypes featured image"&gt;
&lt;/a&gt;
&lt;div class="absolute inset-0 pointer-events-none bg-gradient-to-t from-black/10 via-transparent to-transparent opacity-0 group-hover:opacity-100 transition-opacity duration-300"&gt;&lt;/div&gt;
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&lt;div class="p-8 space-y-4"&gt;
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&lt;a href="https://tanigawalab.org/tags/uk-biobank/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
UK Biobank
&lt;/span&gt;
&lt;/a&gt;
&lt;a href="https://tanigawalab.org/tags/phenotyping/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Phenotyping
&lt;/span&gt;
&lt;/a&gt;
&lt;a href="https://tanigawalab.org/tags/latent-components/"&gt;
&lt;span class="inline-block px-2 py-1 bg-gray-100 dark:bg-gray-700 text-gray-700 dark:text-gray-300 text-xs rounded"&gt;
Latent Components
&lt;/span&gt;
&lt;/a&gt;
&lt;span class="inline-block px-2 py-1 text-gray-500 dark:text-gray-400 text-xs"&gt;
+1 more
&lt;/span&gt;
&lt;/div&gt;
&lt;h3 id="card-title-25754c58734bea9449eac92e150166c6" class="text-xl font-bold tracking-tight text-zinc-900 dark:text-zinc-100 group-hover:text-blue-600 dark:group-hover:text-blue-400 transition-colors duration-200 leading-tight"&gt;
&lt;a href="https://tanigawalab.org/publications/2021/degas-bbj/" class="hover:underline"&gt;
A cross-population atlas of genetic associations for 220 human phenotypes
&lt;/a&gt;
&lt;/h3&gt;
&lt;p class="text-zinc-600 dark:text-zinc-400 text-base leading-relaxed line-clamp-3"&gt;
Using a set of GWAS summary statistics of diseases characterized from both European (UK Biobank and FinnGen) and East Asian (Biobank Japan) populations, we dissected latent DeGAs …
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&lt;time class="hidden sm:inline whitespace-nowrap" datetime="2021-09-30"&gt;
Sep 30, 2021
&lt;/time&gt;
&lt;span class="hidden sm:inline opacity-40"&gt;•&lt;/span&gt;
&lt;span class="hidden sm:inline whitespace-nowrap"&gt;1 min read&lt;/span&gt;
&lt;/div&gt;
&lt;div class="pt-2 border-t border-zinc-200/50 dark:border-zinc-700/50"&gt;
&lt;a href="https://tanigawalab.org/publications/2021/degas-bbj/" class="inline-flex items-center gap-2 text-primary-600 dark:text-primary-400 hover:text-primary-700 dark:hover:text-primary-300 font-medium text-sm transition-all duration-300 group/link"&gt;
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