Author

Andrew Tam

Stanford Medicine

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 2

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Approach:statistical model· 2 Research Focus:benchmarking· 1 Research Focus:database / resource· 1 Research Focus:deconvolution· 1 Organism:human· 1 Research Focus:software / tool· 1

Frequent Co-Authors

Shane Lofgren· 2 shared Aurelie Tomczak· 1 shared Charles Liu· 1 shared Cole A. Deisseroth· 1 shared Edgar G. EnglemaniD· 1 shared Erika BongeniD· 1 shared Erika Bongen· 1 shared Francesco VallaniaiD· 1 shared

Activity by Year

2016-2017 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 25 mutual co-author links

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2 shared papersBioinformatics

Shane Lofgren

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2 papers

Recent·Most cited

Leveraging heterogeneity across multiple data sets increases accuracy of cell-mixture deconvolution and reduces biological and technical biases

Francesco Vallania, Andrew Tam, Shane Lofgren, Steven A. Schaffert, Tej Deepak Azad, Erika Bongen, Meia Alsup, Michael N. Alonso, Mark M. Davis, Edgar G. Engleman, Purvesh Khatri

This paper introduces immunoStates, a basis matrix that reduces biological and technical biases in cell-mixture deconvolution by incorporating diverse disease states and microarray platforms.

bioRxiv · Oct 20, 2017 · PreprintBioinformatics

Empowering Multi-Cohort Gene Expression Analysis to Increase Reproducibility

Winston A. Haynes, Francesco Vallania, Charles Liu, Erika Bongen, Aurelie Tomczak, Marta Andres-Terrè, Shane Lofgren, Andrew Tam, Cole A. Deisseroth, Matthew D. Li, Timothy E. Sweeney, Purvesh Khatri

The paper presents a pipeline and web application for multi-cohort gene expression analysis to improve reproducibility across diverse populations.

bioRxiv · Aug 25, 2016 · PreprintBioinformatics