Research

OVERVIEW: Throughout my doctoral and postdoctoral career, I have always been motivated by biological, medical or environmental problems and related features and/or constraints of the data. As an environmental epidemiologist and biostatistician, I have been involved in development of novel methodology as well as application of existing methodologies to complex problems. Specifically during my postdoctoral tenure, I have worked on problems related to air pollution exposure, environmental epidemiology and gut microbial communities, in context of chronic diseases.

RESEARCH INTERESTS:

Environmental health: Some of my interests in research on environmental health are as follows:

a) Assessment of exposure to environmental pollutants in Indian children and impact on early development.

b) Air pollution exposure assessment using hybrid models, machine learning and satellite data.

c) Associations of air pollution with cardio-metabolic health outcomes.

Methodological problems: These are more theoretical areas of interest that I am working on

a) Causal inferential methods.

b) Compositional data structures.

Human microbiome: Research on human microbiome has gained momentum over the last decade with numerous research projects deciphering the myriad roles of microbiome in human health and diseases. Some of my interests in microbiome research are as follows:

a) Impact of gut microbiome on human health and diseases, especially in the Indian context.

b) Study of breast milk microbiome and associations with malnutrition.

c) Development of statistical methodologies to analyze interactions between microbiome and environmental pollutants.

R codes:

Analysis of Composition of Microbiomes (ANCOM) is a methodology to detect differentially abundant taxa in microbial surveys. The code from the original article (Mandal S, Treuren WV, White RA, Eggesbø M, Knight R & Peddada SD. (2015) Analysis of Composition of Microbiomes (ANCOM): A novel method for studying microbial composition, Microbial Ecology in Health and Diseases; 26: 27663.) has now been updated to include repeated measures, covariates and longitudinal analysis. The code and documentation can be downloaded from the git repository.

Code for ANCOM 2.0 and its documentation can be downloaded from the Git repository: ANCOM git repository