Computational Biologist. University of Pittsburgh.
Joined July 2018
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Maria Chikina retweeted
Just posted manuscript and code for Trellis, an autoformalization system that aims to take a math paper in LaTeX and output a complete formalization in Lean.
Link has manuscript, code, and viewers with formalizations of recent Ramsey theory breakthroughs.
math.cmu.edu/~wes/trellis.ph…
Voters expressed genuine grievances, and while change is rarely immediate, this outcome may still signal shifts that align the economy more closely with the needs of the people. And that’s an aspiration we can all share.
Democracy, though not always a direct reflection of our ideals, remains a system responsive to collective concerns, even if indirectly.
Many are feeling the weight of the election's outcome. As we process this, let's focus on what we can control: our work, connections with friends and family, and sources of personal fulfillment.
Our work benchmarking proportion estimation methods (genomebiology.biomedcentral.…) finds BayesPrism (nature.com/articles/s43018-0…) among the top performers. We introduce a fast re-implementation InstaPrism: same accuracy, orders of magnitude faster! academic.oup.com/bioinformat…
Maria Chikina retweeted
A 🧵 on some of my intuitions/priors about the genetics of complex and molecular traits in humans (i.e. what I think of as typical), largely motivated by GWAS/QTL studies over the past decade [citing papers with nice figures where possible]
Can someone explain Fig 2 of nature.com/articles/s41576-0…. Why do some nascent RNA techniques give signal past the transcription end site and others don't.
Hopefully this in depth evaluation will pave the way for more accurate personalized gene expression models. We will surely need more data and likely different models and training paradigms.
Interested in using deep learning to predict the impact of genetic variation on gene expression? In our pre-print we investigate how well this can be done currently . Joint work with wonderful colleagues @ChikinaLab, Alex (@LXandR_ ), and others.
biorxiv.org/content/10.1101/…
In our new paper embopress.org/doi/full/10.15… we show that unlike gene expression methylation changes persist for months after infection and could be used to predict infection timing. Great effort by @WayneMao1.
If you need to deconvolve bulk RNAseq data and like BayesPrism (tinyurl.com/bdzddefv) consider InstaPrism (tinyurl.com/2p8s7rcj). Same results but much faster.
We just posted a new preprint on benchmarking deconvolution methods. With an appropriately realistic simulation we get highly counter-intuitive results. The problem is far from being completely solved! biorxiv.org/content/10.1101/…
Maria Chikina retweeted
Here Today, Gone Tomorrow: How (Some) Mammals Lost Their Body Hair
new release on lab publication from @KowalczykAmanda and @ChikinaLab
healthcare.utah.edu/publicaf… via @UofUHealth
Our new paper with @NathanClark111 and @KowalczykAmanda looking at mammalian sparse hair phenotype is now online. elifesciences.org/articles/7…
Maria Chikina retweeted
New preprint with @ChikinaLab:
"The paradoxical nature of easily improvable evidence"
When trying to reason about available evidence which is filtered through the lens of publication bias, what you *don't* see can be as informative as what you do see.
1/2
arxiv.org/abs/2205.14016
When considering doing a correlation analysis, a useful thought experiment is to imagine the conclusion for every possible outcome (+, -, NS). This avoids the trap of only accepting the results that reinforce one’s prior and discarding others with some post-hoc explanation.
Maria Chikina retweeted
This thread on a recent paper from @ProfEmilyOster and others is making the rounds.
It is an extremely critical thread employing strong language, questioning the basic judgement and statistical understanding of the authors.
A quick, polite thread with some comments on this.1/12
At a time when many comments from just a few months ago have aged badly this timeless quote from Bertrand Russell is both inspirational and comforting. Stick to the facts, respect those that disagree and you are sure to have few regrets.
Russell's "message to the future" was perhaps never timelier than now.
youtube.com/watch?v=ihaB8AFO…
Maria Chikina retweeted
Happy to announce our recent paper with @ChikinaLab, @jcmattingly, and Alan Frieze on new Markov chain significance tests in the context of redistricting problems.
It includes examples from the 2019 Common Cause v. Lewis case in North Carolina.
tandfonline.com/doi/full/10.…
