In the few years since its initial application, massively parallel cDNA sequencing, or RNA-
seq, has allowed many advances in the characterization and quantification of …

Background Early application of second-generation sequencing technologies to transcript
quantitation (RNA-seq) has hinted at a vast mammalian transcriptome, including transcripts …

RNA-seq experiments generate reads derived not only from mature RNA transcripts but also
from pre-mRNA. Here we present a computational approach called exon-intron split analysis …

Although RNA-seq is a powerful tool, the considerable time and cost associated with library
construction has limited its utilization for various applications. RNAtag-Seq, an approach to …

To the Editor—As single-cell RNA sequencing (scRNA-seq) becomes widespread,
accessible and scalable computational pipelines for data analysis are needed. We introduce …

A recently developed technique called RNA Sequencing (RNA‐Seq) uses massively
parallel sequencing to allow transcriptome analyses of genomes at a far higher resolution …

Next-generation RNA-sequencing (RNA-Seq) is rapidly outcompeting microarrays as the
technology of choice for whole-transcriptome studies. However, the bioinformatics skills …

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 …

RNA sequencing (RNA-seq) offers a snapshot of cellular RNA populations, but not temporal
information about the sequenced RNA. Here we report TimeLapse-seq, which uses …

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 …