Author

Aaron Schein

Columbia UniversityORCID 0000-0002-5507-2904Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Research Focus:cell-cell communication· 1 Research Focus:database / resource· 1 Research Focus:software / tool· 1 Assay:spatial transcriptomics· 1 Approach:statistical model· 1

Frequent Co-Authors

Data Science Teamlab· 1 shared James Strong· 1 shared Jeffrey F. QuinniD· 1 shared Jiayi FaniD· 1 shared John C. HoodiD· 1 shared Kenny Kwok Hei YuiD· 1 shared Patrick FlahertyiD· 1 shared Shai He· 1 shared

Activity by Year

2021-2026 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 1, 2026

Decoding Multicellular Communication Motifs from Spatial Transcriptomics with ALARMIST

Jiayi Fan, John C. Hood, James Strong…·Wesley Tansey

ALARMIST identifies multicellular communication motifs in spatial transcriptomics data, revealing microenvironmental drivers of tumor progression in lung and brain cancers.

DOI 10.64898/2026.05.21.726986

humanspatial transcriptomics

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BioinformaticsThe Annals of Applied StatisticsPeer-reviewedJun 1, 2021

A Bayesian Nonparametric Model for Inferring Subclonal Populations from Structured DNA Sequencing Data

Shai He, Aaron Schein, Vishal Sarsani, Patrick Flaherty

This paper introduces a Bayesian nonparametric model to infer subclonal populations from structured DNA sequencing data, showing improved performance over existing methods.

1 citation

humanwhole-exome sequencing

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