About Fellow

University of Pittsburgh, Pittsburgh, USA

National Cancer Institute, Bethesda, USA

National Institute of Biomedical Genomics, Kalyani

I was heading for a career in engineering or medicine like most science students of my generation. By some turn of events, I ended up joining the Indian Statistical Institute (ISI, Kolkata), pursuing Statistics - a subject I had no idea about. The decision was mostly due to my general interest in Mathematics and the formidable reputation of the Institute. During the next five years, I was fortunate to receive exceptional training in Statistics and Probability from some great teachers at ISI. Primarily, I would mention the name of Prof. Probal Chaudhuri whose teaching influenced me the most. Thanks to them, I quickly became fascinated by the subject and its wide applicability. I realized that Statistics and Probability constitute a way of thinking and reasoning in any scientific discipline rather than being a set of tools or techniques to be learnt. ISI is also a hub of inter-disciplinary teaching and research activity. I was drawn to one particular discipline - Statistical Genetics, primarily due to my interest in Genetics and Biology since high school days. Motivated by the teaching of Prof. Partha Majumder and Prof. Saurabh Ghosh, I decided to pursue a Ph.D. in this area and moved to the Department of Human Genetics at the University of Pittsburgh. There, I got introduced to the basics of molecular genetics and complex human diseases. During my Ph.D. research on score-based tests for QTL mapping in pedigrees with my advisor Prof. Eleanor Feingold and another mentor Prof. Daniel E. Weeks, I learnt the nuts and bolts of methodology development in statistical genetics. I learnt to design large-scale computer simulations of genetic data to evaluate statistical methods and also to build user-friendly software to make new methods accessible to the research community. For my post-doc, I was fortunate to be associated with Dr. Nilanjan Chatterjee a leading statistical geneticist and the Biostatistics Branch at the DCEG, NCI (NIH) engaged in Genome-wide Association Studies (GWAS) and related front line genomics research on various cancers. My post-doc research on gene-gene interactions and subsequently on heterogeneity-aware meta-analysis had a broad scope of applicability. This has been reflected in large numbers of downloads of our software packages by various research groups, many of whom regularly contact us for various issues. After the post-doc I returned to India and joined the National Institute of Biomedical Genomics (NIBMG) a new but vibrant genomics institute having a significant focus on statistical and computational genomics.

Towards the end of my post-doc and through my initial years at NIBMG, the field of complex disease genomics was seeing a gradual shift from the hugely successful GWAS and micro-array gene-expression studies to Next Generation Sequencing (NGS) studies, epigenomic, metabolomics and proteomic studies. While a shift towards finer-resolution omics studies and multi-omic studies is inevitable and also desirable, I am among those who believe that we are yet to recover the information from GWAS to the fullest extent. Also, there is a continuing need for flexible statistical methods to link the large amount of data being generated from various omics platforms to discover causal factors and mechanisms that affect the susceptibility to complex diseases. The current project stems from my motivation to help scientists glean maximal information from these large datasets and make meaningful biological conclusions without getting lost amid false-positives. In the process I hope to contribute towards unravelling the genomic processes involved in complex human diseases. The Intermediate Fellowship from Wellcome Trust/DBT India-Alliance will serve as a huge encouragement for me and also provide the much needed support to build an independent research program.