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Identification of aberrant gene expression in RNA-seq data. Read count expectations are modeled by an autoencoder to control for confounders in the data. Given these expectations, the RNA-seq read counts are assumed to follow a negative binomial distribution with a gene-specific dispersion. Outliers are then identified as read counts that significantly deviate from this distribution. Furthermore, OUTRIDER provides useful plotting functions to analyze and visualize the results.
Package details |
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Author | Felix Brechtmann [aut], Christian Mertes [aut, cre], Agne Matuseviciute [aut], Michaela Fee Müller [ctb], Vicente Yepez [aut], Julien Gagneur [aut] |
Bioconductor views | Alignment GeneExpression Genetics ImmunoOncology RNASeq Sequencing Transcriptomics |
Maintainer | Christian Mertes <mertes@in.tum.de> |
License | MIT + file LICENSE |
Version | 1.8.0 |
URL | https://github.com/gagneurlab/OUTRIDER |
Package repository | View on Bioconductor |
Installation |
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