A Novel Bayesian Outlier Score Based on the Negative Binomial Distribution for Detecting Aberrantly Expressed Genes in RNA-Seq Gene Expression Count Data

<p>The Negative Binomial distribution (NBD) is used for modeling many types of count data, including gene expression counts obtained by RNA sequencing technologies (RNA-Seq). Finding outliers in this type of data has been shown in recent research to help in identifying rare genetic disorders i...

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Bibliographic Details
Main Author:	Edin Salkovic (16891479) (author)
Other Authors:	Halima Bensmail (10400) (author)
Published:	2021
Subjects:	Biological sciences Bioinformatics and computational biology Genetics Information and computing sciences Data management and data science Mathematical sciences Statistics Data models Gene expression Bayes methods Computational modeling Anomaly detection Dispersion Sequential analysis Bayesian model Bayesian outlier score Gibbs sampling Mendelian disorder Negative binomial distribution Outlier detection Rare disease RNA-Seq
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A Novel Bayesian Outlier Score Based on the Negative Binomial Distribution for Detecting Aberrantly Expressed Genes in RNA-Seq Gene Expression Count Data

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