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).
Keywords for this software
References in zbMATH (referenced in 3 articles )
Showing results 1 to 3 of 3.
- Cleynen, A.; Robin, S.: Comparing change-point location in independent series (2016)
- Cleynen, Alice; Dudoit, Sandrine; Robin, Stéphane: Comparing segmentation methods for genome annotation based on RNA-seq data (2014)
- Datta, Somnath (ed.); Nettleton, Dan (ed.): Statistical analysis of next generation sequencing data (2014)