Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain
the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in
Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles
and JavaScript.
RNA-seq five ways. Research in this Focus issue evaluates the performance of RNA sequencing with an emphasis on large-scale studies involving data generated using multiple sequencing sites, platforms or protocols (pp 903, 915, 926, 888 and 896). Credit: Sam Shlomo Spaeth.
Studies from the RNA Sequencing Quality Control (SEQC) initiative exemplify the kind of experimental groundwork needed to expand RNA-seq into a broader array of basic and translational applications.
The reliability of scientific research is under scrutiny. A recently convened working group proposes cultural adjustments to incentivize better research practices.
Gene therapy companies that pursue high, one-time payments for their products risk a backlash from payors. A better solution may lie in a pay-for-performance model.
The unprecedented weakening of patent rights in the United States undermines necessary incentives for the discovery and development of innovative medicines.
Remove unwanted variation (RUV) is a new statistical method for RNA-seq data normalization that uses control genes or samples to improve differential expression analysis.
The Sequencing Quality Control (SEQC) consortium shows that junction discovery and differential gene expression profiling with RNA-seq can be robust but transcript-level and absolute measurements remain challenging.
For intact RNA, gene expression profiles from rRNA-depletion and poly-A enrichment are similar. In addition, rRNA- depletion enables effective analysis of degraded RNA samples.
A comparison of RNA-seq and microarray data from samples treated with diverse drugs highlights a dependency of cross-platform concordance on treatment effect.
TALEN-induced mutation of all homologous copies of a gene that represses resistance to an important wheat pathogen confers a trait that has eluded plant breeders for decades.
This focus presents the results of the RNA Sequencing Quality Control (SEQC) project of the MicroArray Quality Control (MAQC) Consortium that sought to evaluate the comparability of RNA-seq data from many different laboratories and of assessing different sequencing platforms and data analysis approaches and their performance compared with DNA microarrays. Ultimately, these multi-platform, cross-site studies will enable RNA-seq to be applied more broadly in analyzing large cohorts for discovery research and clinical use.
