Here are some major results obtained in this research project during the past year: Microarray gene expression studies over ordered categories are routinely conducted to gain insights into biological functions of genes and the underlying biological processes. Some common experiments are time-course/dose-response experiments where a tissue or cell-line is exposed for different doses and/or durations of time to a chemical. A goal of such studies is to identify gene expression patterns/profiles over the ordered categories. In some instances data across ordered groups are correlated, for example when repeated measurements are taken over the same subject over time. In this research program we developed methodology that accounts for such correlations. Researchers routinely use historical control data (HCD) when analyzing rodent carcinogenicity data obtained in a particular study. Although the concurrent control group is considered to be the most relevant group to compare with the dose groups, the HCD provides a broader perspective to assist in understanding the significance of the current study. The HCD is used to provide information about the incidences of spontaneous tumors and malignant systemic disorders such as lymphoma and leukemia. In this research program we developed a simple statistical methodology that can be used for comparing the tumor response in the current control group with that of the historical controls. We demonstrate that the commonly used historical range based methodology can result in an unacceptably high false positive rate whereas the proposed method controls the false positive rate at the desired nominal level.

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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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