Author

Katie Partington

University of Washington

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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Approach:experimental assay· 2 Organism:human· 1 Assay:imaging· 1 Assay:proteomics· 1 Research Focus:software / tool· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Douglas M. FowleriD· 2 shared Sriram PendyalaiD· 2 shared Abbye E. McEweniD· 1 shared Alan F. RubiniD· 1 shared Allyssa J. VandiiD· 1 shared Clayton E. FriedmaniD· 1 shared Daniel L. HolmesiD· 1 shared Evan McDermotiD· 1 shared

Activity by Year

2026-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 45 mutual co-author links

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2 shared papersGenomics

Douglas M. FowlerORCID

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Author profile →

2 papers

Recent·Most cited

Image-based, pooled phenotyping reveals multidimensional, disease-specific variant effects

Sriram Pendyala, Katie Partington, Nicholas Bradley, Abbye E. McEwen, Gwenneth Straub, Hyeon-Jin Kim, Shawn Fayer, Daniel L. Holmes, Katherine A. Sitko, Riddhiman K. Garge, Ziyu R. Wang, Melinda K. Wheelock, Allyssa J. Vandi, Rachel L. Powell, Clayton E. Friedman, , Douglas M. Fowler

The paper introduces VIS-seq, an image-based method to assess variant effects on cellular phenotypes, revealing multidimensional variant impacts across different diseases.

Cell · May 12, 2026Peer-reviewedGenomics

STARCall integrates image stitching, alignment, and read calling to enable scalable analysis of in situ sequencing data

Nicholas J. Bradley, Sriram Pendyala, Katie Partington, Douglas M. Fowler

STARCall processes in situ sequencing data by integrating image stitching, alignment, and read calling to improve genotype-to-phenotype mapping with reduced error and increased genotyped cells.

PLoS Computational Biology · Apr 27, 2026Peer-reviewedBioinformatics