Author

Shane P. Simonett

University of Wisconsin–MadisonORCID 0000-0002-9359-7808Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Bioinformatics· 1 Genetics· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 2 Organism:mouse· 2 Assay:ATAC-seq· 1 Research Focus:cell type annotation· 1 Assay:ChIP-seq· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1 Research Focus:fine-mapping· 1

Frequent Co-Authors

Alan AttieiD· 2 shared Donnie S. StapletoniD· 2 shared Kathryn L. SchueleriD· 2 shared Mark P. KelleriD· 2 shared Chenyang DongiD· 1 shared Clifford Dustin RubinsteiniD· 1 shared Derek M. PaveleciD· 1 shared Fulai JiniD· 1 shared

Activity by Year

2021-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersGenetics

Alan AttieORCID

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2 papers

Recent·Most cited

A protocol for locating and counting transgenic sequences from laboratory animals using a map-then-capture (MapCap) sequencing workflow: procedure and application of results.

Sidney S. Dicke, Clifford Dustin Rubinstein, James M. Speers, Mark E. Berres, Derek M. Pavelec, Kathryn L. Schueler, Donnie S. Stapleton, Shane P. Simonett, Mark P. Keller, Alan Attie, Martin T. Zanni

The paper presents a MapCap sequencing workflow to locate and count transgenic sequences in mice, identifying insertion sites and characterizing genetic variations in a diabetes model.

bioRxiv · Jan 13, 2022 · PreprintGenetics

INFIMA leverages multi-omics model organism data to identify effector genes of human GWAS variants

Chenyang Dong, Shane P. Simonett, Sunyoung Shin, Donnie S. Stapleton, Kathryn L. Schueler, Gary A. Churchill, Leina Lu, Xiaoxiao Liu, Fulai Jin, Yan Li, Alan Attie, Mark P. Keller, Sündüz Keleş

INFIMA identifies effector genes of GWAS variants by integrating multi-omics data from mice and applying it to diabetes-associated variants.

Genome biology · Aug 23, 2021Peer-reviewedBioinformatics