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SurfaceGenie: A web-based application for prioritizing cell-type specific marker candidates

View ORCID ProfileMatthew Waas, View ORCID ProfileShana T. Snarrenberg, View ORCID ProfileJack Littrell, View ORCID ProfileRachel A. Jones Lipinski, View ORCID ProfilePolly A. Hansen, View ORCID ProfileJohn A. Corbett, View ORCID ProfileRebekah L. Gundry
doi: https://doi.org/10.1101/575969
Matthew Waas
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Shana T. Snarrenberg
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Jack Littrell
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Rachel A. Jones Lipinski
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Polly A. Hansen
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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John A. Corbett
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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Rebekah L. Gundry
1Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
2Center for Biomedical Mass Spectrometry Research, Medical College of Wisconsin, Milwaukee, WI 53226, USA
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  • For correspondence: rgundry@mcw.edu
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Abstract

Cell surface proteins play critical roles in a wide range of biological functions and disease processes through mediation of contacts and signals between a cell and its environment. Owing to their biological significance and accessibility, cell surface proteins are attractive targets for developing tools and strategies to identify, study, and manipulate specific cell types of interest. Applications ranging from immunophenotyping and immunotherapy to targeted drug delivery and in vivo imaging are enabled by exploitation of cell-type specific surface proteins. Despite their utility and relevance, the unique combination of molecules present at the cell surface are not yet described for most cell types. While modern mass spectrometry approaches have proven invaluable for generating discovery-driven, empirically derived snapshot views of surface proteins, significant challenges remain when analyzing these often-large datasets for the purpose of identifying candidate markers that are most applicable for downstream applications. To overcome these challenges, we developed GenieScore, a prioritization metric that integrates a consensus-based prediction of cell surface localization with user-input data to rank-order candidate cell-type specific surface markers. In this report, we outline the development of this prioritization strategy and demonstrate its utility for analyzing human and rodent data from proteomic and transcriptomic experiments in the areas of cancer, stem cell, and islet biology. The calculation of GenieScores, as well as additional scoring algorithm permutations that enable prioritization of co-expressed and intracellular cell-type specific candidate markers, is made accessible via the freely available SurfaceGenie web-application at www.cellsurfer.net/surfacegenie.

Footnotes

  • Additional analyses, figures and data are included. Additional permutations to the GenieScore metric are included.

  • http://www.cellsurfer.net/surfacegenie

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC 4.0 International license.
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Posted May 24, 2019.
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SurfaceGenie: A web-based application for prioritizing cell-type specific marker candidates
Matthew Waas, Shana T. Snarrenberg, Jack Littrell, Rachel A. Jones Lipinski, Polly A. Hansen, John A. Corbett, Rebekah L. Gundry
bioRxiv 575969; doi: https://doi.org/10.1101/575969
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SurfaceGenie: A web-based application for prioritizing cell-type specific marker candidates
Matthew Waas, Shana T. Snarrenberg, Jack Littrell, Rachel A. Jones Lipinski, Polly A. Hansen, John A. Corbett, Rebekah L. Gundry
bioRxiv 575969; doi: https://doi.org/10.1101/575969

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