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  Email:   sb1

 Present Position:  Associate Professor
                               Intermediate Fellow of Wellcome Trust/DBT India Alliance

 Highest educational Qualification:  Ph.D.



As a statistical geneticist, I develop statistical and computational methods for analysis of genomic data such as genome-wide association (GWAS) and gene-expression data. The ‘curse of dimensionality’ presents a challenge for the analysis and interpretation of these huge omics datasets. I am particularly interested in statistical tools that are used to overcome issues arising from high-dimensional nature of genomic data, such as multiple-testing, meta-analysis and pathway/ enrichment-analysis methods. Currently, our group is involved in developing methodology and software that can help elucidate genetic factors underlying complex diseases using ‘integrative statistical modelling’ of genomic data from multiple sources (such as GWAS, gene-expression and eQTL data). We are also interested in developing methods that can flexibly incorporate prior knowledge from various biological databases to improve power of genomic studies.

In the past, I worked on robust statistical methodologies for linkage and association mapping of quantitative trait loci (QTLs), analysing genetic data from case-control studies, with emphasis on gene-gene and gene-environment interactions, pathway analysis and also on meta-analysis of heterogeneous GWAS data. I continue to work on extending some of my work on meta-analysis of heterogeneous traits for detection of pleiotropic genes and variants.


Selected Publications:


  • S Biswas, S., Pal, S., & Bhattacharjee, S*. (2017). A Regression-based Framework for Scalable Pathway-guided Search in Genome-wide Association Studies. bioRxiv, 241265.
  • Sengupta D, Guha U, Bhattacharjee S*, Sengupta M*: Association of 12 polymorphic variants conferring genetic risk to lung cancer in Indian population: An extensive meta-analysis. Environ Mol Mutagen. 2017 Dec;58(9):688-700. doi: 10.1002/em.22149. Epub 2017 Oct 27. [*Corresponding Authors]
  • Cara L. Carty, Samsiddhi Bhattacharjee, Jeff Haessler, Iona Cheng, Lucia A. Hindorff, Vanita Aroda, Christopher S. Carlson, Chun-Nan Hsu, Lynne Wilkens, Simin Liu, Elizabeth Selvin, Rebecca Jackson, Kari E. North, Ulrike Peters, James S. Pankow, Nilanjan Chatterjee and Charles Kooperberg: Comparative Analysis of Metabolic Syndrome Components in over 15,000 African Americans Identifies Pleiotropic Variants: Results from the PAGE Study. Circ Cardiovasc Genet. published online July 14, 2014.
  • Samsiddhi Bhattacharjee, Preetha Rajaraman, Kevin B Jacobs, William A Wheeler, Beatrice S Melin, Patricia Hartge, GliomanScan Consortium, Meredith Yeager, Charles C Chung, Stephen J Chanock, Nilanjan Chatterjee: A subset-based approach improves power and interpretation for the combined-analysis of genetic association studies of heterogeneous traits. Am J Hum Genet 2012, May 4;90(5):821-835.            
  • Samsiddhi Bhattacharjee, Zhaoming Wang, Julia Ciampa, Peter Kraft, Stephen Chanock, Kai Yu, Nilanjan Chatterjee: Using Principal Components of Genetic Variation for Robust and Powerful Detection of Gene-Gene Interactions in Case-Control and Case-Only Studies, Am J Hum Genet 2010 Mar 12;86(3):331-42.
  • Bhattacharjee S, Kuo CL, Mukhopadhyay NM, Brock GN, Weeks DE , Feingold EF: Robust score statistics for QTL linkage analysis, Am J Hum Genet 2008 Mar;82(3):567-582.