TY - JOUR
AU - Smyth, Gordon K.
AB - [This article reviews the statistical theory underlying the edgeR software package for differential expression of RNA-seq data. Negative binomial models are used to capture the quadratic mean-variance relationship that can be observed in RNA-seq data. Conditional likelihood methods are used to avoid bias when estimating the level of variation. Empirical Bayes methods are used to allow gene-specific variation estimates even when the number of replicate samples is very small. Generalized linear models are used to accommodate arbitrarily complex designs. A key feature of the edgeR package is the use of weighted likelihood methods to implement a flexible empirical Bayes approach in the absence of easily tractable sampling distributions. The methodology is implemented in flexible software that is easy to use even for users who are not professional statisticians or bioinformaticians. The software is part of the Bioconductor project.]
TI - Statistical Analysis of Next Generation Sequencing Data: Differential Expression Analysis of Complex RNA-seq Experiments Using edgeR
DA - 2014-06-17
UR - https://www.deepdyve.com/lp/springer-journals/statistical-analysis-of-next-generation-sequencing-data-differential-MJ9kIIjw2l
DP - DeepDyve
ER -