A normalization method based on variance and median adjustment for massive mRNA polyadenylation data

Author(s): Guoli Ji, Ying Wang, MingchenWu, Yangzi Zhang, Xiaohui Wu

This paper proposed a normalizationmethod based on minimumvariance and median adjustment (MVM), and then made a comprehensive comparison of three normalization methods including DESeq, TMMand MVM. In this study, the MVM method was evaluated using polyadenylation [poly(A)] data and gene expression data fromArabidopsis by ways of empirical statistical criterias of mean square error (MSE) and Kolmogorov-Smirnov (K-S) statistic. Experimental results demonstrated the high performance ofMVMmethod in that it could accurately remove the systematic bias and make the distributions of normalized data stable.

Share this       

Share this Page.

Table of Contents

Scimago Journal Rank

izmir escort izmir escort bursa escort antalya escort izmir escort porno porno izle türk porno eskişehir escort bartın escort burdur escort izmir escort bursa escort porno indir izle escort izmir