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SPECS: A non-parameteric method to identify tissue-specific molecular features for unbalanced sample groups

View ORCID ProfileCeline Everaert, View ORCID ProfilePieter-Jan Volders, Annelien Morlion, View ORCID ProfileOlivier Thas, Pieter Mestdagh
doi: https://doi.org/10.1101/656397
Celine Everaert
1Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent, Ghent, Belgium
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  • ORCID record for Celine Everaert
  • For correspondence: celine.everaert@ugent.be
Pieter-Jan Volders
1Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent, Ghent, Belgium
3Flemish Institute for Biotechnology, Ghent, Belgium
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Annelien Morlion
1Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent, Ghent, Belgium
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Olivier Thas
4I-Biostat, Hasselt University, Hasselt, Belgium
5National Institute for Applied Statistics Australia (NIASRA), University of Wollongong, Wollongong, Australia
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Pieter Mestdagh
1Center for Medical Genetics, Department of Biomolecular Medicine, Ghent University, Ghent, Belgium
2Cancer Research Institute Ghent, Ghent, Belgium
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Abstract

To understand biology and differences among various tissues or cell types, one typically searches for molecular features that display characteristic abundance patterns. Several specificity metrics have been introduced to identify tissue-specific molecular features, but these either require an equal number of replicates per tissue or they can’t handle replicates at all. We describe a non-parametric specificity score that is compatible with unequal sample group sizes. To demonstrate its usefulness, the specificity score was calculated on all GTEx samples, detecting known and novel tissue-specific genes. A webtool was developed to browse these results for genes or tissues of interest. An example python implementation of SPECS is available at https://github.ugent.be/ceeverae/SPECs. The precalculated SPECS results on the GTEx data are available through a user-friendly browser at specs.cmgg.be.

Footnotes

  • https://specs.cmgg.be

  • https://github.ugent.be/ceeverae/SPECs

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 4.0 International license.
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Posted May 31, 2019.
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SPECS: A non-parameteric method to identify tissue-specific molecular features for unbalanced sample groups
Celine Everaert, Pieter-Jan Volders, Annelien Morlion, Olivier Thas, Pieter Mestdagh
bioRxiv 656397; doi: https://doi.org/10.1101/656397
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SPECS: A non-parameteric method to identify tissue-specific molecular features for unbalanced sample groups
Celine Everaert, Pieter-Jan Volders, Annelien Morlion, Olivier Thas, Pieter Mestdagh
bioRxiv 656397; doi: https://doi.org/10.1101/656397

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