Author

Eric W. Stawiski

GenentechORCID 0000-0002-9387-6719Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Organism:human· 2 Assay:whole-genome sequencing· 2 Research Focus:cell type annotation· 1 Research Focus:database / resource· 1 Organism:mouse· 1 Assay:scRNA-seq· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Somasekar SeshagiriiD· 3 shared Deepak Tanneeru· 2 shared J. Fah SathirapongsasutiiD· 2 shared Ravi Kr GuptaiD· 2 shared Sameer PhalkeiD· 2 shared Aakrosh RataniD· 1 shared Abhijit Chowdhury· 1 shared Adam S. ButterworthiD· 1 shared

Activity by Year

2019-2021 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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3 shared papersGenetics

Somasekar SeshagiriORCID

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3 papers

Recent·Most cited

GeneticsCommunications BiologyPeer-reviewedApr 12, 2021

Human ACE2 receptor polymorphisms predict SARS-CoV-2 susceptibility

Kushal Suryamohan, Devan C. Diwanji, Eric W. Stawiski…·Somasekar Seshagiri

This study identifies ACE2 receptor polymorphisms that may influence susceptibility to SARS-CoV-2 by altering the interaction between ACE2 and the viral S-protein.

299 citationstop 1%

humanwhole-genome sequencing

𝕏 PostBluesky

GenomicsbioRxivPreprintOct 2, 2020

South Asian patient population genetics reveal strong founder effects and high rates of homozygosity - new resources for precision medicine

Jeffrey D. Wall, J. Fah Sathirapongsasuti, Ravi Kr Gupta…·Andrew S. Peterson

The paper characterizes the genetic structure of South Asian populations, identifies founder effects and high homozygosity, and develops a custom SNP array for genetic studies in the region.

5 citations

humanwhole-genome sequencing

𝕏 PostBluesky

BioinformaticsGenesPeer-reviewedJul 12, 2019

SCINA: Semi-Supervised Analysis of Single Cells in silico

Ze Zhang, Danni Luo, Xue Yun Zhong…·Tao Wang

SCINA is a semi-supervised model for analyzing scRNA-Seq and flow cytometry data, improving accuracy and efficiency over unsupervised methods by leveraging gene signatures.

288 citationstop 2%

mousescRNA-seq

𝕏 PostBluesky