A popular approach for comparing gene expression levels between (replicated) conditions of RNA sequencing data relies on counting reads that map to features of interest. Within such count-based methods, many flexible and advanced statistical approaches now exist and offer the ability to adjust for covariates (e.g. batch effects). Often, these methods… (More)
DNA methylation, the reversible addition of methyl groups at CpG dinucleotides, represents an important regulatory layer associated with gene expression. Changed methylation status has been noted across diverse pathological states, including cancer. The rapid development and uptake of microarrays and large scale DNA sequencing has prompted an explosion of… (More)
A response to ‘Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data’ by Rapaport F, Khanin R, Liang Y, Pirun M, Krek A, Zumbo P, Mason CE, Socci ND and Betel D in Genome Biology, 2013, 14:R95
A Correspondence to Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data. CC-BY-NC-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was. Background Statistical methods for determining transcriptional changes between… (More)
CC-BY-ND 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was .
DNA methylation, and specifically the reversible addition of methyl groups at CpG dinu-cleotides genome-wide, represents an important layer that is associated with the regulation of gene expression. In particular, aberrations in the methylation status have been noted across a diverse set of pathological states, including cancer. With the rapid development… (More)