Motivation: RNA-seq has been extensively used for transcriptome study. Quality control (QC)
is critical to ensure that RNA-seq data are of high quality and suitable for subsequent …

Background High-throughput next-generation RNA sequencing has matured into a viable
and powerful method for detecting variations in transcript expression and regulation …

Background RNA-Seq has become one of the most widely used applications based on next-
generation sequencing technology. However, raw RNA-Seq data may have quality issues …

RNA-seq, the application of next-generation sequencing to RNA, provides transcriptome-
wide characterization of cellular activity. Assessment of sequencing performance and library …

Post-sequencing quality control is a crucial component of RNA sequencing (RNA-seq) data
generation and analysis, as sample quality can be affected by sample storage, extraction …

Background Assessing the reliability of experimental replicates (or global alterations
corresponding to different experimental conditions) is a critical step in analyzing RNA-Seq …

Motivation Single-cell RNA sequencing (scRNA-seq) is increasingly used to study gene
expression at the level of individual cells. However, preparing raw sequence data for further …

Obtaining RNA-seq measurements involves a complex data analytical process with a large
number of competing algorithms as options. There is much debate about which of these …

The sequencing of the full transcriptome (RNA-seq) has become the preferred choice for the
measurement of genome-wide gene expression. Despite its widespread use, challenges …

Ribonucleic acid sequencing (RNA-seq) identifies and quantifies RNA molecules from a
biological sample. Transformation from raw sequencing data to meaningful gene or isoform …