Peter Kraft
Cancer epidemiologist, statistical geneticist, biostatistician. National Cancer Institute, Harvard. Views my own.
- Reposted by Peter KraftInterested in pleiotropy dissection but not sure where to start, which methods are useful, which studies offer illustrative examples, or how to robustly validate your results? Look no further 👀 rdcu.be/eSfAZ
- Reposted by Peter Kraft@ajhgnews.bsky.social sat with Julie-Alexia Dias, MSc, in the latest "Inside AJHG" to discuss her recently published paper, “Evaluating multi-ancestry genome-wide association methods: statistical power, population structure, and practical implications.”➡️ ashg.org/ajhg/inside-... #ASHG #humangenetics
- This was neat work by @nmancuso.bsky.social et al developing and benchmarking a new multi-ancestry fine-mapping method (“SuShiE”). I learned something about the performance of pooled v stratified analyses but still have some Qs. 1/n
- 📢OUT TODAY @natgenet.nature.com 📰Improved multiancestry fine-mapping identifies cis-regulatory variants underlying molecular traits and disease risk. By @zeyunlu.bsky.social, @nmancuso.bsky.social and colleagues. ⬇️ www.nature.com/articles/s41...
- If fine-mapping, mol-QTL, or [fill-in-the-blank]WAS analyses are your jam, do check this paper out, if only for the nice review and assessment of contemporary multi-ancestry fine-mapping methods. If fine-mapping is not your jam, this is gonna get technical & jargony. 2/n
- We just compared pooled versus stratified analysis of GWAS for locus discovery (pubmed.ncbi.nlm.nih.gov/40902600/), so I was particularly interested in the comparisons of SuShiE and other methods that rely on genetic-ancestry-group-stratified analyses to SuSiE applied to the pooled data. 3/n
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View full threadCurious to hear others’ thoughts and experience here! /fin
- Reposted by Peter KraftThe observation that joint analysis can safely improve power strikes me as being a similar observation to that of @genandgenes.bsky.social et al in their Nature 2019 manuscript: www.nature.com/articles/s41...
- Multi-ancestry GWAS can increase power and precision, but how should we analyze them? Pooled or stratified? We answer that question in a paper out today in AJHG, led by Julie Dias and Haoyu Zhang. 1/7 www.cell.com/ajhg/fulltex...
- Through a combination of maths, simulations, and real-data analyses, we show that pooled analysis is generally more powerful than meta-analysis while controlling Type I error rates. 2/7
- Your mileage may vary: power gains and confounding are trait- and context-specific. Our simulations and real-data examples are focused on anthropometry, biomarkers, and complex diseases. Confounding could be more of an issue for socially defined traits (e.g. educational attainment). 3/7
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View full threadThanks to all coauthors (including @madduri on here) for important substantive and technical contributions. 7/7
- Reposted by Peter KraftAn evergreen thread: Race/Ethnicity is *not the same* as genetics, and you can't use Race/Ethnicity as a sort of stand-in for genetics. These two concepts are connected via aspects like skin colour, but the connection is alot less profound and categorical than most people think.
- Reposted by Peter KraftNice blog and good to see this also from the twins/shared environment side. We (with my colleagues in @wittbrodtlab.bsky.social) have tried to tackle the non-additive in experimental settings (in medaka fish) which we can map to human (as the medaka fish are "wild") www.biorxiv.org/content/10.1...
- Reposted by Peter KraftI wrote about gene-gene interactions (epistasis) and the implications for heritability, trait definitions, natural selection, and therapeutic interventions. Biology is clearly full of causal interactions, so why don't we see them in the data? A 🧵:
