Some examples of research conducted in this project: In addition to studying the effects of external environment (chemical and biological) on human health, lately there has been considerable interest among researchers to study the effects of human internal microbial environment. Human body contains large diverse colonies bacteria and they may vary according by location on the body and by age of the person. For example, the composition of bacteria in an infant's gut changes from new born to a toddler. The data on the microbial composition are not the usual Euclidean space data but are constrained to sum to 1. Consequently standard statistical methods such as ANOVA or t-test are not applicable. In this research program we are developing novel statistical procedures for analyzing such complex data. Statistical methodologies are also being developed in this research project for analyzing data obtained from cell-cycle and circadian clock experiments. These new methods make use of the underlying geometry in the data.

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U.S. National Inst of Environ Hlth Scis
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Weiss, Sophie; Xu, Zhenjiang Zech; Peddada, Shyamal et al. (2017) Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome 5:27
Kaul, Abhishek; Davidov, Ori; Peddada, Shyamal D (2017) Structural zeros in high-dimensional data with applications to microbiome studies. Biostatistics :
Mandal, Siddhartha; Godfrey, Keith M; McDonald, Daniel et al. (2016) Fat and vitamin intakes during pregnancy have stronger relations with a pro-inflammatory maternal microbiota than does carbohydrate intake. Microbiome 4:55
Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A et al. (2016) Order restricted inference for oscillatory systems for detecting rhythmic signals. Nucleic Acids Res 44:e163
Rueda, Cristina; Fernández, Miguel A; Barragán, Sandra et al. (2016) Circular piecewise regression with applications to cell-cycle data. Biometrics 72:1266-1274
Grandhi, Anjana; Guo, Wenge; Peddada, Shyamal D (2016) A multiple testing procedure for multi-dimensional pairwise comparisons with application to gene expression studies. BMC Bioinformatics 17:104
Zhao, Haibing; Peddada, Shyamal D; Cui, Xinping (2015) Mixed directional false discovery rate control in multiple pairwise comparisons using weighted p-values. Biom J 57:144-58
Mandal, Siddhartha; Van Treuren, Will; White, Richard A et al. (2015) Analysis of composition of microbiomes: a novel method for studying microbial composition. Microb Ecol Health Dis 26:27663
Barragán, Sandra; Rueda, Cristina; Fernández, Miguel A et al. (2015) Determination of Temporal Order among the Components of an Oscillatory System. PLoS One 10:e0124842
Wu, Michael C; Joubert, Bonnie R; Kuan, Pei-fen et al. (2014) A systematic assessment of normalization approaches for the Infinium 450K methylation platform. Epigenetics 9:318-29

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