Affiliation:
1. Department of Biochemistry, Medical College of Wisconsin, Milwaukee, WI 53226, USA
2. Center for Biomedical Mass Spectrometry Research, Medical College of Wisconsin, Milwaukee, WI 53226, USA
Abstract
Abstract
Motivation
Cell-type-specific surface proteins can be exploited as valuable markers for a range of applications including immunophenotyping live cells, targeted drug delivery and in vivo imaging. Despite their utility and relevance, the unique combination of molecules present at the cell surface are not yet described for most cell types. A significant challenge in analyzing ‘omic’ discovery datasets is the selection of candidate markers that are most applicable for downstream applications.
Results
Here, 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 demonstrate the utility of GenieScore for analyzing human and rodent data from proteomic and transcriptomic experiments in the areas of cancer, stem cell and islet biology. We also demonstrate that permutations of GenieScore, termed IsoGenieScore and OmniGenieScore, can efficiently prioritize co-expressed and intracellular cell-type-specific markers, respectively.
Availability and implementation
Calculation of GenieScores and lookup of SPC scores is made freely accessible via the SurfaceGenie web application: www.cellsurfer.net/surfacegenie.
Contact
Rebekah.gundry@unmc.edu
Supplementary information
Supplementary data are available at Bioinformatics online.
Funder
National Institutes of Health
Juvenile Diabetes Research Foundation
T32 grant
National Institute of General Medical Sciences
Publisher
Oxford University Press (OUP)
Subject
Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability
Cited by
45 articles.
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