About Anaconda Help Download Anaconda

edurand / packages / bioconductor-edaseq

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).

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/edurand/bioconductor-edaseq/badges/version.svg
badge
https://anaconda.org/edurand/bioconductor-edaseq/badges/latest_release_date.svg
badge
https://anaconda.org/edurand/bioconductor-edaseq/badges/latest_release_relative_date.svg
badge
https://anaconda.org/edurand/bioconductor-edaseq/badges/platforms.svg
badge
https://anaconda.org/edurand/bioconductor-edaseq/badges/license.svg
badge
https://anaconda.org/edurand/bioconductor-edaseq/badges/downloads.svg

© 2024 Anaconda, Inc. All Rights Reserved. (v4.0.3) Legal | Privacy Policy