Konrad J. Karczewski

Interpreting genetic variation using large genomic datasets.

About me

I am a Computational Biologist at the Broad Institute in Ben Neale's group working on large-scale analysis of exome sequencing data.

I graduated with a PhD in Biomedical Informatics from Stanford University, advised by Mike Snyder and Stephen Montgomery, and an undergraduate in Molecular Biology from Princeton University, specializing in Quantitative and Computational Biology. My postdocotoral work with Daniel MacArthur focused on loss-of-function variants in humans. I am the co-author of Exploring Personal Genomics, the first inquiry-based guide to understanding and interpreting a personal genome, available from Amazon.

Follow me on Twitter or Github.

Research

My research is focused on assembling and analyzing massive public datasets of genetic variation, and developing novel strategies using these to aid in the interpretation of putative disease variants, in order to better distinguish causal disease variants and improve our understanding of human biology.

Broadly speaking, I am interested in genome sequencing and its future role in our daily lives. With the age of rapidly decreasing sequencing costs, it is not difficult to imagine an age where personal genetic information plays an important role in medicine and daily life. We are constantly discovering more and more of the genetic basis of diseases, but much work has yet to be done in fully explaining the genetic components of disease and other phenotypes.

Selected Publications

Full list available at Google Scholar:

Karczewski KJ, Francioli LC, Tiao G, Cummings BB, Alföldi J, Wang Q, et al., "Variation across 141,456 human exomes and genomes reveals the spectrum of loss-of-function intolerance across human protein-coding genes." bioRxiv. 2019 Jan 29. doi: 10.1101/531210

Martin AR, Karczewski KJ, Kerminen S, Kurki MI, Sarin AP, Artomov M, et al., "Haplotype Sharing Provides Insights into Fine-Scale Population History and Disease in Finland." Am J Hum Genet. 2018 Apr 25. pii: S0002-9297(18)30092-2. doi: 10.1016/j.ajhg.2018.03.003. (bioRxiv. doi: 10.1101/200113).

Karczewski KJ and Snyder M. "Integrative Omics for Health and Disease." Nat Rev Genet. 2018 May; 19(5):299-310. doi: 10.1038/nrg.2018.4.

Karczewski KJ, Weisburd B, Thomas B, Ruderfer DM, Kavanagh D, Hamamsy T, et al., "The ExAC Browser: Displaying reference data information from over 60,000 exomes." Nucleic Acids Res. 2017 Jan 4; 45(D1):D840-D845. doi: 10.1093/nar/gkw971. Epub 2016 Nov 28. (bioRxiv. doi: 10.1101/070581. 2016 Aug 19.)

Lek M, Karczewski KJ*, Minikel EV*, Samocha KE*, Banks E, Fennell T, et al., "Analysis of protein-coding genetic variation in 60,706 humans." Nature. 2016 Aug 17; 536(7616):285-91. doi: 10.1038/nature19057. (bioRxiv. doi: 10.1101/030338. 2015 Oct 30).

Karczewski KJ, Snyder M, Altman RB, Tatonetti NP. "Coherent functional modules improve transcription factor target identification, cooperativity prediction, and disease association." PLoS Genetics. 10(2): e1004122. doi:10.1371/journal.pgen.1004122.s012

Karczewski KJ*, Dudley JT*, Kukurba KR, Chen R, Butte AJ, Montgomery SB, Snyder M. "Systematic functional regulatory assessment of disease-associated variants." Proc Natl Acad Sci U S A. Epub 2013 May 20. doi: 10.1073/pnas.1219099110.

Dudley JT and Karczewski KJ. Exploring Personal Genomics. January 2013. Oxford University Press.

Karczewski KJ*, Tirrell RP*, Tatonetti NP, Dudley JT, Cordero P, Salari K, et al., "Interpretome: A Freely Available, Modular, and Secure Personal Genome Interpretation Engine." Pac Symp Biocomput. Epub 2011 Oct 25. 17:339-350(2012).

Karczewski KJ, Tatonetti NP, Landt SG, Yang X, Slifer T, Altman RB, Snyder M. "Cooperative Transcription Factor Associations Discovered using Regulatory Variation." Proc Natl Acad Sci U S A. 2011 Aug 9;108(32):13353-8. doi: 10.1073/pnas.1103105108. Epub 2011 Jul 26.

Public Projects

gnomAD: The Genome Aggregation Database, dataset and browser.


LOFTEE: loss-of-function variation annotation.


Hail (contributor): open-source library for large-scale data analysis.


Interpretome: A Freely Available, Modular, and Secure Personal Genome Interpretation Engine.

Contact

Email: konradjkarczewski@gmail.com

Follow me on Twitter, Github, or see my Amazon Author Page.