Tanushree Haldar, PhD

Computational/Data Science Researcher

Department of Clinical Pharmacy

[email protected]

533 Parnassus Avenue, Rm 585

UCSF Box 0622

San Francisco, CA 94117

United States

Links

UCSF Profiles

What I do

As a computational and data science research specialist, I perform various biostatistical data analyses to explore the effect and side effect of medicines in a population. I also develop software tools for general applications of our proposed computational methods.

Degrees

PhD, Indian Statistical Institute

MStat, Indian Statistical Institute

BSc, Presidency College, Calcutta University

Research keywords

False Positive Reactions, Genetic Pleiotropy, Models, Genetic, Genetic Heterogeneity, Lipid Metabolism, Alcoholism, Genetic Association Studies, Bayes Theorem, Lipids, Quantitative Trait Loci, Demography, Phenotype, Linkage Disequilibrium, Quantitative Trait, Heritable, Models, Statistical

Publications

Majumdar A, Burch KS, Haldar T, Sankararaman S, Pasaniuc B, Gauderman WJ, Witte JS. A two-step approach to testing overall effect of gene-environment interaction for multiple phenotypes. Bioinformatics. 2021 Jan 16.

Tanushree Haldar, Dipanwita Roy Chowdhury. Design of Hash Function Using Two Dimensional Cellular Automata. . 2020 Nov 26; 1170:33-45.

Oni-Orisan A, Haldar T, Ranatunga DK, Medina MW, Schaefer C, Krauss RM, Iribarren C, Risch N, Hoffmann TJ. The impact of adjusting for baseline in pharmacogenomic genome-wide association studies of quantitative change. NPJ Genom Med. 2020; 5:1.

Saurabh Ghosh, Tanushree Haldar. Statistical challenges in genetic association analyses: Populationbased versus family-based studies. Indian Journal of Genetics and Plant Breeding (The). 2019 Jan 16; 79(01S).

Hoffmann TJ, Theusch E, Haldar T, Ranatunga DK, Jorgenson E, Medina MW, Kvale MN, Kwok PY, Schaefer C, Krauss RM, Iribarren C, Risch N. A large electronic-health-record-based genome-wide study of serum lipids. Nat Genet. 2018 03; 50(3):401-413.

Majumdar A, Haldar T, Bhattacharya S, Witte JS. An efficient Bayesian meta-analysis approach for studying cross-phenotype genetic associations. PLoS Genet. 2018 02; 14(2):e1007139.

Majumdar A, Haldar T, Witte JS. Determining Which Phenotypes Underlie a Pleiotropic Signal. Genet Epidemiol. 2016 07; 40(5):366-81.

Haldar T, Ghosh S. Statistical equivalent of the classical TDT for quantitative traits and multivariate phenotypes. J Genet. 2015 Dec; 94(4):619-28.

Haldar T, Mukhopadhyay I, Ghosh S. A novel transmission-based test of association for multivariate phenotypes: an application to systolic and diastolic blood pressure levels. BMC Proc. 2014; 8(Suppl 1):S71.

Tanushree Haldar, Saumya Chakrabarti. Conflict or Coexistence? A story of big and small retailers*. Review of Development and Change. 2014 Jun 1; 19(1):19-41.

Haldar T, Ghosh S. Effect of population stratification on false positive rates of population-based association analyses of quantitative traits. Ann Hum Genet. 2012 May; 76(3):237-45.

Haldar T, Ghosh S. Power comparison between population-based case-control studies and family-based transmission-disequilibrium tests: An empirical study. Indian J Hum Genet. 2011 May; 17 Suppl 1:S27-31.