EDASeq: Exploratory Data Analysis and Normalization for RNA-Seq

Numerical and graphical summaries of RNA-Seq read data. Within-lane normalization procedures to adjust for GC-content effect (or other gene-level effects) on read counts: loess robust local regression, global-scaling, and full-quantile normalization (Risso et al., 2011). Between-lane normalization procedures to adjust for distributional differences between lanes (e.g., sequencing depth): global-scaling and full-quantile normalization (Bullard et al., 2010).

AuthorDavide Risso [aut, cre, cph], Sandrine Dudoit [aut], Ludwig Geistlinger [ctb]
Date of publicationNone
MaintainerDavide Risso <risso.davide@gmail.com>
LicenseArtistic-2.0
Version2.8.0
https://github.com/drisso/EDASeq

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