Negative binomial modelling is one of the most commonly used statistical tools for analysing
count data in ecology and biodiversity research. This is not surprising given the prevalence …

RNA-seq is a methodology for RNA profiling based on next-generation sequencing that
enables to measure and compare gene expression patterns at unprecedented resolution …

Background Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple
sources, including biological variation in cellular state as well as technical variation …

In comparative high-throughput sequencing assays, a fundamental task is the analysis of
count data, such as read counts per gene in RNA-seq, for evidence of systematic changes …

With age, skeletal muscle stem cells (MuSCs) activate out of quiescence more slowly and
with increased death, leading to defective muscle repair. To explore the molecular …

Motivation: Next-generation sequencing technologies generate millions of short sequence
reads, which are usually aligned to a reference genome. In many applications, the key …

New normal linear modeling strategies are presented for analyzing read counts from RNA-
seq experiments. The voom method estimates the mean-variance relationship of the log …

Motivation: DNA methylation is an epigenetic modification with important roles in many
biological processes and diseases. Bisulfite sequencing (BS-seq) has emerged recently as …

RNA sequencing (RNA-seq) has been rapidly adopted for the profiling of transcriptomes in
many areas of biology, including studies into gene regulation, development and disease. Of …

A basic task in the analysis of count data from RNA-seq is the detection of differentially
expressed genes. The count data are presented as a table which reports, for each sample …