Sile Hu (@fuopen) profile picture

Sile Hu

@fuopen

Interested in stats&pop genetics. He/him. Views are my own

Joined May 2012
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If you are interested in the use of single-cell data to map drivers of infertility, have a look at this preprint from the excellent Ipsita Agarwal and others! biorxiv.org/content/10.64898… We show how unpaired chromosomes generate aneuploidy, and map new genetic drivers.
Large disruptions to mammalian spermatogenesis downstream of genetic perturbations in meiotic...

Large disruptions to mammalian spermatogenesis downstream of genetic perturbations in meiotic...

Fertility in mammalian species depends on the successful pairing of homologous chromosomes, mediated by formation of DNA double-strand breaks and a process of homology search involved in repairing...

biorxiv.org
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New work from us pooling together clinical sequencing data to identify large effect common risk variants for rare cancer types. This included a novel HLA locus that interacts with HPV infection to increase Anal Cancer risk.
Image from Sasha Gusev (@SashaGusevPosts)
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Sile Hu retweeted
Daniel Tabin (@DanTabin) profile picture
Daniel Tabin
@DanTabinApr 18
Very interesting and rich work by @hrushikesh_loya @leo_speidel @simon_r_myers and others has many interesting findings. I want to highlight this figure, which is similar to the model David recently proposed. Can’t wait to read it more deeply
Image from Daniel Tabin (@DanTabin)
Nrken19 (@nrken19) profile pictureNrken19
@nrken19Apr 18
Genome-wide genealogies reveal deep admixtures forming modern humans. Funny name to call the method for "GhostBuster" biorxiv.org/content/10.64898…
Image from Nrken19 (@nrken19)
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Nice article in the New York Times (archive.is/LiQsj) on Akbari et al. Nature finding a large number of novel loci under selection in ancient DNA data. Here's what I wrote when asked for comment:
Image from Sasha Gusev (@SashaGusevPosts)
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New work from our group developing a method to estimate the molecular heritability of longitudinal traits (e.g. disease onset, progression, or death). Many traits appear to be a genetic mixture of onset/liability and progression components. See Kodi's thread for more:
Kodi Taraszka (@KodiTaraszka) profile pictureKodi Taraszka@KodiTaraszkaFeb 23
Excited to share our preprint introducing COXMM! COXMM is a Cox proportional hazard mixed model for estimating the heritability of time-to-event (TTE)/longitudinal traits. 🧵1/10 Work with @SashaGusevPosts and @sr_sankararaman. doi.org/10.64898/2026.02.16.…
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New method from our group for identifying disease-mediating genes using perturb-seq, eQTL, and GWAS data. Check out the thread:
Zeyun Lu 鲁泽沄 (@zeyun_lu) profile pictureZeyun Lu 鲁泽沄@zeyun_luJan 5
Happy to share our new preprint from @SashaGusevPosts and @nmancuso_ labs! We introduce Mr. PEG, a framework integrating perturbational screens, eQTL, and GWAS data to identify mediating genes for complex traits. (1/n) medrxiv.org/content/10.64898…
Integrating perturbational screens, eQTL, and GWAS data identifies mediating genes for complex...

Integrating perturbational screens, eQTL, and GWAS data identifies mediating genes for complex...

Most current GWAS-eQTL approaches prioritize genes whose mediating effects on complex traits act through cis -regulation, while trans -acting genes remain largely underexplored. Recent perturbational...

medrxiv.org
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High false sign rates in transcriptome-wide association studies biorxiv.org/content/10.64898… #biorxiv_genetic
High false sign rates in transcriptome-wide association studies

High false sign rates in transcriptome-wide association studies

Transcriptome-wide association studies (TWAS) are widely used to identify genes involved in complex traits and to infer the direction of gene effects on traits. However, despite their popularity, it...

biorxiv.org
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I wrote about the bizarre case of Herasight, the embryo selection company going all in on eugenics.
Image from Sasha Gusev (@SashaGusevPosts)
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Modern GWAS can identify 1000s of significant hits but it can be hard to turn this into biological insight. I'm excited to share our new work combining genetic associations and Perturb-seq to build interpretable causal graphs, out today in @Nature:
Image from Jonathan Pritchard (@jkpritch)
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Excited to share our latest work on the factors that determine what genes we find (and don't find!) in GWAS and burden tests. We describe a critical concept that we call *specificity*. Led by Jeff Spence and Hakhamanesh Mostafavi:
Hakhamanesh Mostafavi (@Hakha_Most) profile pictureHakhamanesh Mostafavi@Hakha_Most7 Nov 2025
How do GWAS and rare variant burden tests rank gene signals? In new work @Nature with Jeff Spence, @jkpritch, and our wonderful coauthors we find the key factors are what we call Specificity, Length, and Luck! 🧬🧪🧵 nature.com/articles/s41586-0…
Specificity, length and luck drive gene rankings in association studies

Specificity, length and luck drive gene rankings in association studies

Nature - Genetic association tests prioritize candidate genes based on different criteria.

nature.com
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Na Cai (@caina89) profile picture
Na Cai@caina8924 Jul 2025
Very happy to share our new paper now on @medrxivpreprint: “Genetic risk effects act in sets”, a great effort led my PhD student @JolienRietkerk, and performed together with collaborators @andywdahl, @AndrewSchork, @jonathan_flint1 etc. Thread 1/n
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Happy to share that our work from the @nmancuso_ lab is out in @NatureGenet! We developed SuShiE, a multiancestry fine-mapping method for molecular traits. doi.org/10.1038/s41588-025-0…
Improved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits...

Improved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits...

Nature Genetics - SuShiE is a multiancestry fine-mapping method for molecular quantitative trait loci that leverages linkage disequilibrium heterogeneity to improve resolution, infer cross-ancestry...

nature.com
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The HLA region is key to human health, but is often excluded in large-scale GWAS. Informing future studies on its influence, @AJHGNews' latest article reports HLA haplotype-based associations across thousands of diseases: bit.ly/4lrJiXT #ASHG @jkpritch
Image from ASHG (@GeneticsSociety)
Image from ASHG (@GeneticsSociety)
Image from ASHG (@GeneticsSociety)
Image from ASHG (@GeneticsSociety)
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Grok 4 is the first time, in my experience, that an AI has been able to solve difficult, real-world engineering questions where the answers cannot be found anywhere on the Internet or in books. And it will get much better.
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Postdoc position in my group in Tokyo! Please get in touch if you are interested. And happy to discuss projects - ranging from developing new methods to analysis of new genomes that we are now sequencing in the lab. riken.jp/en/careers/research… Lab page: speidellab.github.io/
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Mutation-selection-drift balance models of complex diseases biorxiv.org/content/10.1101/… #biorxiv_genetic
Mutation-selection-drift balance models of complex diseases

Mutation-selection-drift balance models of complex diseases

Genetic variation that influences complex disease susceptibility is introduced into the population by mutation and removed by natural selection and genetic drift. This mutation-selection-drift-bala...

biorxiv.org
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I'm very happy that our paper on admixture in deep human evolution is out now in Nature Genetics! nature.com/articles/s41588-0… Thanks very much to my PhD supervisors Aylwyn Scally and Richard Durbin for their support throughout
A structured coalescent model reveals deep ancestral structure shared by all modern humans

A structured coalescent model reveals deep ancestral structure shared by all modern humans

Nature Genetics - The cobraa model extends the pairwise sequentially Markovian coalescent to identify structured population history by examination of the model transition matrix. Applied to human...

nature.com
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VERY excited to announce a pre-print that represents the culmination of several years of work*: “On ARGs, pedigrees, and genetic relatedness matrices” doi.org/10.1101/2025.03.03.6… Led by @BrieucLehmann with contributions from @epigenci @LukeAnderTroc @jeromekelleher @petrelharp
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A General Framework for Branch Length Estimation in Ancestral Recombination Graphs biorxiv.org/content/10.1101/… #biorxiv_evobio
A General Framework for Branch Length Estimation in Ancestral Recombination Graphs

A General Framework for Branch Length Estimation in Ancestral Recombination Graphs

Inference of Ancestral Recombination Graphs (ARGs) is of central interest in the analysis of genomic variation. ARGs can be specified in terms of topologies and coalescence times. The coalescence...

biorxiv.org
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Happy New Year! Our Twigstats paper is now out! nature.com/articles/s41586-0…
High-resolution genomic history of early medieval Europe

High-resolution genomic history of early medieval Europe

Nature - Twigstats, a method for ancestry reconstruction, provides high-resolution genetic histories and movement patterns of people living in Europe during the first millennium ce.

nature.com
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