bioconductor-edaseq
Exploratory Data Analysis and Normalization for RNA-Seq
Exploratory Data Analysis and Normalization for RNA-Seq
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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).
Summary
Exploratory Data Analysis and Normalization for RNA-Seq
Last Updated
Dec 28, 2024 at 20:29
License
Artistic-2.0
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65.5K
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