Author

Sayan Mukherjee

Primary ORCID profile (0000-0002-6715-3920 · 16 papers)Unclaimed ORCID profile · follow to get notified of new preprints

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Same name, identified by ORCID

Sayan MukherjeeiD16 papers · Duke University

Biology Disciplines

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Bioinformatics· 3 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Organism:human· 3 Assay:metagenomics· 3 Research Focus:benchmarking· 2 Research Focus:cell-cell communication· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Research Focus:gene regulatory network inference· 1

Frequent Co-Authors

Lawrence A David· 3 shared Justin D Silverman· 2 shared Alex D Washburne· 1 shared Alex Washburne· 1 shared Alkes L Price· 1 shared Dominic J Bennett· 1 shared Eran HalperiniD· 1 shared Gaurav Bhatia· 1 shared

Activity by Year

2016-2018 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 19 mutual co-author links

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3 shared papersBioinformatics

Lawrence A David

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Author profile →

4 papers

Recent·Most cited

Statistical Considerations in the Design and Analysis of Longitudinal Microbiome Studies

Justin D Silverman, Liat Shenhav, Eran Halperin, Sayan Mukherjee, Lawrence A David

This paper reviews statistical challenges in longitudinal microbiome studies and provides guidelines for design and analysis.

bioRxiv · Oct 20, 2018 · PreprintMicrobiology

Phylogenetic factorization of compositional data

Alex D Washburne, Justin D Silverman, Jonathan Leff, Dominic J Bennett, John L Darcy, Sayan Mukherjee, NOAH FIERER, Lawrence A David

The paper introduces phylofactorization, a method to identify phylogenetic factors driving microbial community composition patterns using compositional data from human and soil samples.

bioRxiv · Sep 12, 2016Bioinformatics

A phylogenetic transform enhances analysis of compositional microbiota data

Justin D Silverman, Alex Washburne, Sayan Mukherjee, Lawrence A David

The paper introduces the PhILR transform to improve analysis of microbiota data by incorporating phylogenetic information, enhancing statistical accuracy and revealing evolutionary patterns in microbial communities.

bioRxiv · Aug 31, 2016Bioinformatics

Fast principal components analysis reveals convergent evolution of ADH1B gene in Europe and East Asia

Kevin J Galinsky, Gaurav Bhatia, Po-Ru Loh, Stoyan Georgiev, Sayan Mukherjee, Nick J Patterson, Alkes L Price

The paper introduces FastPCA, a method for detecting natural selection by analyzing principal components, and identifies new selection signals including ADH1B in Europeans and East Asians.

The American Journal of Human Genetics · Mar 1, 2016Peer-reviewedBioinformatics