Taotao Tan
@doubletaotan.bsky.social
Computational biology & statistical genetics. 3rd year graduate student @ Baylor College of Medicine
https://jasontan-code.github.io
https://jasontan-code.github.io
Reposted by Taotao Tan
We're excited to introduce Tractor-Mix, our new method for GWAS in admixed cohorts with relatedness, led by the fantastic @doubletaotan.bsky.social! Read the full preprint here: www.medrxiv.org/content/10.1...
Thanks to all our amazing collaborators who helped make this work possible!
Thanks to all our amazing collaborators who helped make this work possible!
June 9, 2025 at 6:31 PM
We're excited to introduce Tractor-Mix, our new method for GWAS in admixed cohorts with relatedness, led by the fantastic @doubletaotan.bsky.social! Read the full preprint here: www.medrxiv.org/content/10.1...
Thanks to all our amazing collaborators who helped make this work possible!
Thanks to all our amazing collaborators who helped make this work possible!
Reposted by Taotao Tan
www.biorxiv.org/content/10.1...
📄 New preprint alert! 📄
@helenyslin.bsky.social benchmarked polygenic scores (PGS) using genotyping arrays vs whole-genome sequencing (WGS) across traits & populations in @AllofUsResearch. What’s the best approach? The answer is… it depends! 🧵⬇️
📄 New preprint alert! 📄
@helenyslin.bsky.social benchmarked polygenic scores (PGS) using genotyping arrays vs whole-genome sequencing (WGS) across traits & populations in @AllofUsResearch. What’s the best approach? The answer is… it depends! 🧵⬇️
Differential performance of polygenic prediction across traits and populations depending on genotype discovery approach
Polygenic scores (PGS) are widely used for estimating genetic predisposition to complex traits by aggregating the effects of common variants into a single measure. They hold promise in identifying ind...
www.biorxiv.org
March 20, 2025 at 2:53 PM
www.biorxiv.org/content/10.1...
📄 New preprint alert! 📄
@helenyslin.bsky.social benchmarked polygenic scores (PGS) using genotyping arrays vs whole-genome sequencing (WGS) across traits & populations in @AllofUsResearch. What’s the best approach? The answer is… it depends! 🧵⬇️
📄 New preprint alert! 📄
@helenyslin.bsky.social benchmarked polygenic scores (PGS) using genotyping arrays vs whole-genome sequencing (WGS) across traits & populations in @AllofUsResearch. What’s the best approach? The answer is… it depends! 🧵⬇️
Reposted by Taotao Tan
Differential performance of polygenic prediction across traits and populations depending on genotype discovery approach https://www.biorxiv.org/content/10.1101/2025.03.18.644029v1
March 19, 2025 at 6:32 AM
Differential performance of polygenic prediction across traits and populations depending on genotype discovery approach https://www.biorxiv.org/content/10.1101/2025.03.18.644029v1
Reposted by Taotao Tan
What do GWAS and rare variant burden tests discover, and why?
Do these studies find the most IMPORTANT genes? If not, how DO they rank genes?
Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬)
www.biorxiv.org/content/10.1...
Do these studies find the most IMPORTANT genes? If not, how DO they rank genes?
Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬)
www.biorxiv.org/content/10.1...
Specificity, length, and luck: How genes are prioritized by rare and common variant association studies
Standard genome-wide association studies (GWAS) and rare variant burden tests are essential tools for identifying trait-relevant genes. Although these methods are conceptually similar, we show by anal...
www.biorxiv.org
December 17, 2024 at 7:05 AM
What do GWAS and rare variant burden tests discover, and why?
Do these studies find the most IMPORTANT genes? If not, how DO they rank genes?
Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬)
www.biorxiv.org/content/10.1...
Do these studies find the most IMPORTANT genes? If not, how DO they rank genes?
Here we present a surprising result: these studies actually test for SPECIFICITY! A 🧵on what this means... (🧪🧬)
www.biorxiv.org/content/10.1...