Author

Suyash S. Shringarpure

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· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Organism:human· 2 Research Focus:variant calling· 2 Assay:whole-genome sequencing· 2 Research Focus:batch correction / integration· 1 Research Focus:differential expression· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Behalf of the CAAPA consortium· 1 shared Carlos D. Bustamante· 1 shared Carlos D. BustamanteiD· 1 shared David H. Alexander· 1 shared Francisco M. De La Vega· 1 shared Kathleen C. Barnes· 1 shared Kenneth L. LangeiD· 1 shared Margaret A. Taub· 1 shared

Activity by Year

2016-2016 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 24 mutual co-author links

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1 shared paperBioinformatics

Behalf of the CAAPA consortium

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2 papers

Recent·Most cited

Comparing multi- and single-sample variant calls to improve variant call sets from deep coverage whole-genome sequencing data

Suyash S. Shringarpure, Rasika A. Mathias, Ryan D. Hernandez, Timothy D. O’Connor, Zachary A. Szpiech, Raul Torres, Francisco M. De La Vega, Carlos D. Bustamante, Kathleen C. Barnes, Margaret A. Taub, Behalf of the CAAPA consortium

The paper improves variant call sets from deep coverage whole-genome sequencing data by comparing multi- and single-sample variant calls using a Random Forest classifier trained on genotype array data.

bioRxiv · Sep 30, 2016 · PreprintBioinformatics

Efficient analysis of large datasets and sex bias with ADMIXTURE

Suyash S. Shringarpure, Carlos D. Bustamante, Kenneth L. Lange, David H. Alexander

The paper improves ADMIXTURE software for faster ancestry inference and better handling of sex-biased admixture in large genomic datasets.

bioRxiv · Feb 10, 2016Genomics