@xiaoting_l

Research Associate at Department of Applied Mathematics and Theoretical Physics, University of Cambridge; PhD from @Columbia_bio

Cambridge, England
Joined October 2018
Super excited to share my lab's latest work on quantifying the private information leakage from single cell count matrices. Led by very first postdoc in the g2lab, brilliant @BioConorWalker, we showed that individuals can be reidentified 1/n cell.com/cell/fulltext/S0092…
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Great to see this paper published! @xiaoting_l and @HarmenBussemkr developed a really creative way to robustly quantify TF activity, which we then used as a phenotype in GWAS.
Excited to share that our paper came out in Cell Genomics last week. We developed a model to estimate TF regulatory activity from GTEx RNA-seq data and mapped genetic variants (“aQTLs”) predictive of this virtual trait.
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Thrilled to see that this work is finally out. Huge thanks to @HarmenBussemkr and @tuuliel_lab for the invaluable mentorship and guidance throughout
Excited to share that our paper came out in Cell Genomics last week. We developed a model to estimate TF regulatory activity from GTEx RNA-seq data and mapped genetic variants (“aQTLs”) predictive of this virtual trait.
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So excited our “aQTLs” work is on bioRxiv! Extremely grateful for the mentorship of @HarmenBussemkr and for the collaboration with @tuuliel_lab.
Excited to share a new preprint by my PhD student @xiaoting_l from our wonderful collaboration with the @tuuliel_lab on genetic determinants of TF activity ("aQTLs"). tinyurl.com/mwthyxeb (1/n)
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Our new biophysically interpretable machine learning approach has been published by @NatureBiotech. This was a great collaborative effort. go.nature.com/3lAJlTZ bussemakerlab.org #ProBound
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Xiaoting Li from the Bussemaker lab at Columbia presenting our collaborative project: Identifying genetic regulatory variants that affect transcription factor activity. New method for estimating TF activity from expression data applied to GTEx for GWAS mapping #BoG22
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