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BlackSheep: A Bioconductor and Bioconda package for differential extreme value analysis

View ORCID ProfileLili Blumenberg, View ORCID ProfileEmily Kawaler, View ORCID ProfileMacIntosh Cornwell, Shaleigh Smith, View ORCID ProfileKelly Ruggles, View ORCID ProfileDavid Fenyö
doi: https://doi.org/10.1101/825067
Lili Blumenberg
1Sackler Institute, Department of Medicine, New York University School of Medicine, New York, NY, USA
2Division of Translational Medicine, Department of Medicine, New York University School of Medicine, New York, NY, USA
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Emily Kawaler
1Sackler Institute, Department of Medicine, New York University School of Medicine, New York, NY, USA
3Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA
4Institute for Systems Genetics, New York University School of Medicine, New York, NY, USA
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MacIntosh Cornwell
1Sackler Institute, Department of Medicine, New York University School of Medicine, New York, NY, USA
2Division of Translational Medicine, Department of Medicine, New York University School of Medicine, New York, NY, USA
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Shaleigh Smith
1Sackler Institute, Department of Medicine, New York University School of Medicine, New York, NY, USA
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Kelly Ruggles
2Division of Translational Medicine, Department of Medicine, New York University School of Medicine, New York, NY, USA
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  • For correspondence: David@FenyoLab.org kelly.ruggles@nyulangone.org
David Fenyö
3Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY, USA
4Institute for Systems Genetics, New York University School of Medicine, New York, NY, USA
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  • For correspondence: David@FenyoLab.org kelly.ruggles@nyulangone.org
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Abstract

Unbiased assays such as shotgun proteomics and RNA-seq provide high-resolution molecular characterization of tumors. These assays measure molecules with highly varied distributions, making interpretation and hypothesis testing challenging. Samples with the most extreme measurements for a molecule can reveal the most interesting biological insights, yet are often excluded from analysis. Furthermore, rare disease subtypes are, by definition, underrepresented in cancer cohorts. To provide a strategy for identifying molecules aberrantly enriched in small sample cohorts, we present BlackSheep--a package for non-parametric description and differential analysis of genome-wide data, available at https://github.com/ruggleslab/blackSheep. BlackSheep is a complementary tool to other differential expression analysis methods that may be underpowered when analyzing small subgroups in a larger cohort.

Footnotes

  • Figure 1 was slightly modified. The manuscript was edited slightly for clarity. Figures were moved to the middle for ease of reading.

  • https://github.com/ruggleslab/blackSheep

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 November 11, 2019.
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BlackSheep: A Bioconductor and Bioconda package for differential extreme value analysis
Lili Blumenberg, Emily Kawaler, MacIntosh Cornwell, Shaleigh Smith, Kelly Ruggles, David Fenyö
bioRxiv 825067; doi: https://doi.org/10.1101/825067
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BlackSheep: A Bioconductor and Bioconda package for differential extreme value analysis
Lili Blumenberg, Emily Kawaler, MacIntosh Cornwell, Shaleigh Smith, Kelly Ruggles, David Fenyö
bioRxiv 825067; doi: https://doi.org/10.1101/825067

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