Professor and Chair, Biostatistics
7126 Public Health, 130 DeSoto Street, Pittsburgh, PA 15261
Primary Phone: 967-838-9357
Web site: https://www.publichealth.pitt.edu/home/directory/shyamal-peddada
In this research program, we develop broadly applicable statistical methods that are motivated by applications in biomedical sciences, such as microbiome, genomics, high throughput screening assays, toxicology, oscillatory systems such as circadian clock and cell-cycle, etc. Two important features of the methods developed in our research program are (a) they take into account the underlying structure or constraints in the scientific problem, and (b) they are applicable to high dimensional data. We also collaborate extensively with researchers on a wide range of projects where we often use the methods developed in this research program. We are currently collaborating on a variety of projects relating to human microbiome, toxicology, and genomics.
1983 | University of Pittsburgh, Pittsburgh, PA | PhD, Statistics
1981 | University of Pittsburgh, Pittsburgh, PA | MA, Statistics
1980 | Indian Agricultural Research Institute, New Delhi, India | MSc, Agricultural Statistics
1977 | University of Delhi, Delhi, India | BSc (HONS), Mathematics
A. Theory, Methods and Applications
B. Collaborative Research
The following software was developed in this research program and is freely available to download from https://www.niehs.nih.gov/research/resources/software/biostatistics/index.cfm.
• Larriba Y, Rueda C, Fernandez MA, Peddada SD. Order restricted inference for oscillatorysystems for detecting rhythmic signals. Nucleic Acids Research doi: 10.1093/nar/gkw771 (2016).
• Analysis of Compositional Microbiomes (ANCOM) data
• Mandal S, Van Treuren W, White RA, Eggesbø M, Knight R, and Peddada SD. Analysis of composition of microbiomes: a novel method for studying microbial composition. Microbial Ecology in Health and Disease, 26, 1 – 7 (2015).
• R Code for Estimating of Global Relative Order of Peak Expression Satisfied by a Set of Oscillatory Genes(28KB)
• Barragán S, Rueda C, Fernández MA, Peddada SD (2015) Determination of Temporal Order among the Components of an Oscillatory System. PLoS ONE 10(7): e0124842. https://doi.org/10.1371/journal.pone.0124842
• ORIOGEN 4.01 - Order Restricted Inference for Ordered Gene Expression and Multiple Pairwise Comparisons:
In many applications, such as in dose-response studies or time-course experiments, researchers are interested in testing for specific inequality constraints or patterns among the means of experimental groups. This R package is designed to test for such inequality patterns using a robust residual bootstrap based methodology which does not require the data to be normally distributed. Furthermore, this software can also handle the situation when covariates and/or random effects are present. Thus, for example, this package can be used in the context of repeated measurement designs with covariates. This package comes with a user friendly graphical interface so no programming is necessary to run this package. All the user needs to do is to provide input source of the data and select options from the interface.
• Jelsema C, Peddada SD. An R Package for Linear Mixed Effects Models under Inequality Constraints. Journal of Statistical Software doi: 10.18637/jss.v075.i01 (2016).