Biomedical and Translational Informatics Laboratory
The mission of the Ritchie Lab is to improve our understanding of the underlying genetic architecture of common diseases such as cancer, diabetes, cardiovascular disease, and pharmacogenomic traits among others.
Latest News
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Rasika Venkatesh has a paper out today from one of her collaborations with Shefali’s lab
Wednesday, 21 August 2024 16:41
Congratulations to Rasika Venkatesh who has a paper out today from one of her collaborations with Shefali’s lab. Read more >> -
David Zhang's paper "Protein-truncating variant in APOL3 increases chronic kidney disease risk in epistasis with APOL1 risk alleles" was accepted to JCI Insights
Thursday, 15 August 2024 16:00
David Zhang's paper "Protein-truncating variant in APOL3 increases chronic kidney disease risk in epistasis with APOL1 risk alleles" was accepted to JCI Insights. Also congrats to Latrice who is a coauthor on this paper with us. -
Sunday, 28 July 2024 14:07
Karl, Rasika, and Rachit's project on evaluating the performance of LLMs in the context of pharmacogenetics was accepted for a talk (and a poster) at the Asis & Pacific Bioiformatics Joint Conference! -
Monday, 20 May 2024 18:21
Rasika Venkatesh successfully passed the PhD candidacy exams
Latest Software Releases
- Biofilter 2.4.3: The latest update for Biofilter is available. New in this version:
- updated from Python2 to Python3
- updated LOKI loaders
- fixed a bug in removing redundant results
- BioBin 2.3.0: The latest update for BioBin is now available. New in this version:
- Improved genomic build detection and handling
- Improved output formatting
- New runtime options to better control the processing of sample, phenotype and VCF files
Recent Publications
- Tong, B. et al. (2024). Class-Balanced Deep Learning with Adaptive Vector Scaling Loss for Dementia Stage Detection. In: Cao, X., Xu, X., Rekik, I., Cui, Z., Ouyang, X. (eds) Machine Learning in Medical Imaging. MLMI 2023. Lecture Notes in Computer Science, vol 14349. Springer, Cham. https://doi.org/10.1007/978-3-031-45676-3_15
- Compher, C. W., Quinn, R., Haslam, R., Bader, E., Weaver, J., Dudek, S., Ritchie, M. D., Lewis, J. D., & Wu, G. D. (2024). Penn Healthy Diet survey: pilot validation and scoring. The British Journal of Nutrition., 131(1), 156–162. https://doi.org/10.1017/S0007114523001642
- Li, R., Benz, L., Duan, R., Denny, J. C., Hakonarson, H., Mosley, J. D., Smoller, J. W., Wei, W.-Q., Ritchie, M. D., Moore, J. H., & Chen, Y. (2024). MixWAS: An efficient distributed algorithm for mixed-outcomes genome-wide association studies. Medrxiv. https://doi.org/10.1101/2024.01.09.24301073
- Verma, S. S., Gudiseva, H. V., Chavali, V. R. M., Salowe, R. J., Bradford, Y., Guare, L., Lucas, A., Collins, D. W., Vrathasha, V., Nair, R. M., Rathi, S., Zhao, B., He, J., Lee, R., Zenebe-Gete, S., Bowman, A. S., McHugh, C. P., Zody, M. C., Pistilli, M., … O’Brien, J. M. (2024). A multi-cohort genome-wide association study in African ancestry individuals reveals risk loci for primary open-angle glaucoma. Cell, 187(2). https://doi.org/10.1016/j.cell.2023.12.006
- Chae, A., Yao, M. S., Sagreiya, H., Goldberg, A. D., Chatterjee, N., MacLean, M. T., Duda, J., Elahi, A., Borthakur, A., Ritchie, M. D., Rader, D., Kahn, C. E., Witschey, W. R., & Gee, J. C. (2024). Strategies for implementing machine learning algorithms in the clinical practice of Radiology. Radiology, 310(1). https://doi.org/10.1148/radiol.223170
