We propose an Asymmetric Within-Sample Transformation (AWST) to regularize RNA-seq read counts and reduce the effect of noise on the classification of samples. AWST comprises two main steps: standardization and smoothing. These steps transform gene expression data to reduce the noise of the lowly expressed features, which suffer from background effects and low signal-to-noise ratio, and the influence of the highly expressed features, which may be the result of amplification bias and other experimental artifacts.
Package details |
|
---|---|
Bioconductor views | GeneExpression Normalization RNASeq Sequencing SingleCell Software Transcriptomics |
Maintainer | |
License | MIT + file LICENSE |
Version | 1.11.1 |
URL | https://github.com/drisso/awst |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.