An analysis of the effects of reference sample selection in the normalization of RNA-SEQ data

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dc.contributor.advisor Begum, Munni, 1970-
dc.contributor.author Patterson, Brandon
dc.date.accessioned 2015-06-15T18:06:04Z
dc.date.available 2015-06-15T18:06:04Z
dc.date.issued 2015-05
dc.identifier.other A-362
dc.identifier.uri http://cardinalscholar.bsu.edu/handle/123456789/199735
dc.description.abstract Normalization of read counts is an important data processing step in the detection of differentially expressed (DE) genes between two treatments in RNA-Seq data. One popular method of normalization, the trimmed mean of M-values (TMM) approach, requires the selection of a reference sample to compare all other samples against. This selection is often made somewhat arbitrarily, and can lead to unnecessary variability in DE detection results. We propose a simple method of normalization vector averaging to reduce this variability while sacrificing minimal performance. en_US
dc.description.sponsorship Honors College en_US
dc.subject.lcsh Mathematics.
dc.title An analysis of the effects of reference sample selection in the normalization of RNA-SEQ data en_US
dc.type Undergraduate senior honors thesis.
dc.description.degree Thesis (B.?) en_US
dc.identifier.cardcat-url http://liblink.bsu.edu/catkey/1775987


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  • Undergraduate Honors Theses [5615]
    Honors theses submitted to the Honors College by Ball State University undergraduate students in partial fulfillment of degree requirements.

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