Tarjinder Singh, PhD
Tarjinder (TJ) Singh, PhD, is an Assistant Professor in Computational and Statistical Genomics at the Columbia University Department of Psychiatry, with joint appointments at the Mortimer B. Zuckerman Mind Brain Behavior Institute and the New York State Psychiatric Institute. He is also an Associate Member at the New York Genome Center.
He joined Columbia University and the New York Genome Center from the Analytical and Translational Unit of the Massachusetts General Hospital and the Stanley Center for Psychiatric Research at the Broad Institute of Harvard and MIT. There, he worked as a post-doctoral fellow (2017 - 2020) and as an Instructor at Harvard Medical School (2020 - 2022) with Dr. Mark Daly and Dr. Benjamin Neale. He obtained his PhD in Biological Sciences from the University of Cambridge, England, and the Wellcome Trust Sanger Institute working with Dr. Jeffrey Barrett in 2016. He received his Bachelor’s Degree in Biology, Mathematics, and Economics at Williams College in 2012.
- Assistant Professor of Computational and Statistical Genomics (in Psychiatry)
Credentials & Experience
Education & Training
- BA, 2012 Biology, Mathematics, and Economics, Williams College, USA
- PhD, 2016 Cambridge University and the Wellcome Trust Sanger Institute, UK.
- Fellowship: 2020 Massachusetts General Hospital, Harvard Medical School, and the Broad Institute of Harvard and MIT
Using genomics and big data to uncover insights into the etiology of mental illnesses.
Dr. Tarjinder Singh's team focuses on generating, analyzing, and integrating genetic and functional data to understand the causes of mental illnesses. As part of global collaborative efforts, he has identified specific genes associated with severe psychiatric disorders. With statistical genetics as a foundation, his team develops new approaches to analyze sequence data from hundreds of thousands of individuals. Using results from genetic and functional, his team hopes to build specific biological hypotheses on disease pathogenesis that lead to more effective therapeutic development.
- Analysis of Human Sequence Data
- Functional Interpretation of Genetic Risk
- Genetic Etiology of Psychiatric Disorders
- Genome-wide Association Studies
- Statistical genetics
Singh, T., Poterba, T., Curtis, D., ..., SCHEMA consortium, ..., Neale B. M., and Daly M. J. (2022). Rare coding variants in ten genes confer substantial risk for schizophrenia. Nature 2022 Apr;604(7906):509-516. https://doi.org/10.1038/s41586-022-04556-w
Satterstrom, F. K., Walters, R. K., Singh, T., et al. Autism spectrum disorder and attention deficit hyperactivity disorder have a similar burden of rare protein-truncating variants. Nature Neuroscience. 22, 1961–1965 (2019).
Heyne, H. O., Singh, T. et al. De novo variants in neurodevelopmental disorders with epilepsy. Nat. Genet. 50, 1048–1053 (2018).[TS1]
Singh, T., Walters, J. T. R., Johnstone, M., Curtis, D., Suvisaari, J., Torniainen, M., Rees, E., ..., INTERVAL Study, UK10K Consortium, Palotie, A., Sullivan, P. F., O’Donovan, M. C., Owen M. J., Barrett, J. C. (2017). The contribution of rare variants to risk of schizophrenia in individuals with and without intellectual disability. Nature Genetics, 49:11671173.
Singh, T., Kurki, M. I., Curtis, D., Purcell, S. M., Crooks, L., McRae, J., Suvisaari, J., Chheda, H., ..., Swedish Schizophrenia Study, INTERVAL Study, DDD Study, UK10K Consortium, Sullivan, P. F., Hurles, M. E., O’Donovan, M. C., Palotie, A., Owen, M. J., Barrett, J. C. (2016). Rare loss- of-function variants in SETD1A are associated with schizophrenia and developmental disorders. Nature Neuroscience, 19:571-577.
For a full list of publications, please visit Google Scholar