Author

Meia Alsup

Stanford Medicine

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Bioinformatics· 1

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Assay:bulk RNA-seq· 1 Research Focus:deconvolution· 1 Organism:human· 1 Approach:statistical model· 1

Frequent Co-Authors

Andrew Tam· 1 shared Edgar G. EnglemaniD· 1 shared Erika BongeniD· 1 shared Francesco VallaniaiD· 1 shared Mark M. DavisiD· 1 shared Michael N. AlonsoiD· 1 shared Purvesh KhatriiD· 1 shared Shane Lofgren· 1 shared

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2017-2017 · peak 1/yr

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1 shared paperBioinformatics

Andrew Tam

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1 paper

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