We use large-scale, high-throughput and next generation sequencing based genomic data to investigate how DNA sequence variants contribute to complex human diseases. The research in my group engages sophisticated statistical methodology and the use of high-performance computing resources for novel genetics analyses and methods development. The overarching goal of my laboratory is to develop and evaluate biological hypotheses for answering how human genetic variation can affect metabolic and neurodegenerative conditions – for example, why (a) humans have different genetic susceptibility to these complex diseases, and (b) find SNPs and structural variants that associate with the disease of interest, (c) unravel the physiological pathways relevant to disease being studied, (d) unravel causality and shared genetic basis of these disorders, (e) how gene gene interactions contribute to shapinh complex phenotypes and (f) how evolution have shaped these genomic characteristics; using integrative bioinformatics, statistical, and computational methods. We seek to to integrate methylation, RNA expression and other -omics data in order to develop more powerful genomics-based predictors for such diseases.

Overall, my group’s research is aimed to better understand the shared genetic architecture between metabolic disorders and of psychiatric and neurodegenerative disorders, including genetic overlap between different disorders (i.e. pleiotropy) and genetic and phenotypic heterogeneity within disorders in Indian population.