Author

Emily F. Davis-Marcisak

Johns Hopkins UniversityORCID 0000-0001-8624-1013Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Developmental Biology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

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Assay:scRNA-seq· 3 Approach:statistical model· 3 Research Focus:clustering· 2 Research Focus:differential expression· 2 Research Focus:gene regulatory network inference· 2 Organism:human· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1

Frequent Co-Authors

Elana Judith FertigiD· 3 shared Genevieve Stein-O’BrieniD· 3 shared Loyal A. GoffiD· 3 shared Elizabeth M. JaffeeiD· 2 shared Thomas D. Sherman· 2 shared Alexander C. HopkinsiD· 1 shared Alexander V. FavoroviD· 1 shared Ashley P. TsangiD· 1 shared

Activity by Year

2018-2023 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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3 shared papersSystems Biology

Elana Judith FertigORCID

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3 papers

Recent·Most cited

Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R, and GenePattern Notebook implementations of CoGAPS

Jeanette Johnson, Ashley P. Tsang, Jacob T. Mitchell, David L. Zhou, Julia Bowden, Emily F. Davis-Marcisak, Thomas D. Sherman, Ted Liefeld, Melanie Loth, Loyal A. Goff, Jacquelyn W. Zimmerman, Ben Kinny-Köster, Elizabeth M. Jaffee, Pablo Tamayo, Jill P. Mesirov, , Genevieve Stein-O’Brien

The paper introduces computational tools for NMF analysis of single-cell RNA-seq data, demonstrating their use in quantifying cell state transitions in pancreatic cancer.

Nature Protocols · Nov 21, 2023Peer-reviewedSystems Biology

Expression variation analysis for tumor heterogeneity in single-cell RNA-sequencing data

Emily F. Davis-Marcisak, Pranay Orugunta, Genevieve Stein-O’Brien, Sidharth V. Puram, Evanthia T. Roussos Torres, Alexander C. Hopkins, Elizabeth M. Jaffee, Alexander V. Favorov, Bahman Afsari, Loyal A. Goff, Elana Judith Fertig

This paper introduces EVAsc, a method to analyze expression variation in scRNA-seq data to quantify tumor heterogeneity across cell types, subtypes, and patients.

bioRxiv · Nov 27, 2018 · PreprintBioinformatics

Comprehensive analysis of retinal development at single cell resolution identifies NFI factors as essential for mitotic exit and specification of late-born cells

Brian S. Clark, Genevieve Stein-O’Brien, Fion Shiau, Gabrielle Heather Cannon, Emily F. Davis-Marcisak, Thomas D. Sherman, Fatemeh Rajaii, Rebecca E. James-Esposito, Richard M. Gronostajski, Elana Judith Fertig, Loyal A. Goff, Seth Blackshaw

The paper uses single-cell RNA sequencing to analyze retinal development stages and identifies NFI factors as regulators of late progenitor cell specification and mitotic exit.

bioRxiv · Jul 30, 2018 · PreprintDevelopmental Biology