Im-Lab
Our goal is to develop quantitative and computational methods and tools to sift through the vast amounts of genomic data with the goal of making discoveries that can be translated into clinical practice.
Latest News and Announcements
Winners of U4C Challenge leverage PrediXcan
Two of the 5 winners of NCI's "Up for a Challenge? (U4C) Stimulating Innovation in Breast Cancer Genetic Epidemiology" leveraged PrediXcan (individual and summary based) approach for their discoveries.https://epi.grants.cancer.gov/events/u4c/winners.html
MetaXcan manuscript on bioRxiv
MetaXcan: Summary Statistics Based Gene-Level Association Method Infers Accurate PrediXcan Results [link]
PrediXcan among top 3 in #TBICRI16/methods
We are elated that our PrediXcan paper was chosen one of the top three papers in the category of "Methods for Genetic Discovery" in the "Translational Bioinformatics 2016: The Year in Review" list. This was curated by Russ Altman and the AMIA Student Working Group. Congratulations to everyone who worked hard to get this done. [link]
Find our manuscript on genetic architecture of gene expression across tissues on BioRxiv
Survey of the Heritability and Sparsity of Gene Expression Traits Across Human Tissues [link]
Find our Bipolar Disorder manuscript on BioRxiv
A preprint of our manuascript "Genetic predictors of gene expression associated with risk of bipolar disorder" was posted on BioRxiv [link]
Multiple Openings in Genomic Data Science Lab
Are you passionate about science and know how to navigate big data? Or want to learn how to tame big data in a collegial environment? Then join me in building a Genomic Data Science Laboratory.
Robert Elston Best Paper Award for our OmicKriging paper
Plaque autographed by Robert Elston himself! [link]
NIMH R01 awarded
Imlab was awarded with the NIMH R01 grant for "developing advanced computational, bioinformatic, and statistical tools to determine the functional relevance of genetic variants associated with mental disorders of complex etiologies identified through genome-wide association or sequencing studies".
http://grants.nih.gov/grants/guide/pa-files/PAR-13-391.html
Now hiring pre and post doctoral candidates
We are looking for a highly motivated quantitative scientist interested in directing their career toward interdisciplinary biomedical research. This is a great time to veer your career into this rapidly growing area since we are facing a shortage of scientists with the analytical and computational background to take advantage of the enormous amount of genomic and health data generated. Two large initiatives Big Data to Knowledge and Precision Medicine by the NIH show the commitment of the US government in investing in these areas.
Invited talk at the ASHG Wed 10/7/11am-1pm
Haky will be giving a talk on MetaXcan in the invited session "Secure, Efficient, and Scalable Computational Genetics via Summary Statistics" at the ASHG meeting in Baltimore (Wednesday, October 07, 2015 from 11am to 1pm).
Press release for PrediXcan
Kevin Jiang's blog post: http://sciencelife.uchospitals.edu/2015/08/10/new-computational-method-predicts-genes-likely-to-be-causal-in-disease/
The press release can be found here: http://www.uchospitals.edu/news/2015/20150810-predixcan.html
Some places that have rerun the press release:
PrediXcan published online in Nature Genetics
A gene-based association method for mapping traits using reference transcriptome data
Eric R Gamazon, Heather E Wheeler, Kaanan P Shah, Sahar V Mozaffari, Keston Aquino-Michaels, Robert J Carroll, Anne E Eyler, Joshua C Denny, GTEx Consortium, Dan L Nicolae, Nancy J Cox & Hae Kyung Im
PrediXcan manuscript accepted for publication in Nature Genetics
PrediXcan is a gene-based association test that prioritizes genes that are likely to be causal for the phenotype.
https://github.com/hakyimlab/PrediXcan
http://biorxiv.org/content/early/2015/06/17/020164
NIDA P50 Pilot Grant Awarded
We were awarded one of the Pilot Project Grant Awards for NIDA P50 Grant P50DA037844 to build a web resource to integrate discoveries in rat and human phenotypes.
Poly-Omic Prediction of Complex Traits: OmicKring online
Our paper 'Poly-Omic Prediction of Complex Traits: OmicKring' is available online
DRTC pilot grant awarded
The Diabetes Research and Training Center has awarded a Pilot and Feasibility grant for our proposal entitled "Systems Approach to Discover Biological Mechanisms of Complex Traits". P30 DK020595
K12 Award
Haky has been selected as a University of Chicago Paul Calabresi Clinical Oncology K12 Scholar. The award period is 08/01/13 to 07/31/15. K12CA139160.