Single-cell RNA sequencing (scRNA-seq) is an increasingly popular platform to study heterogeneity at the single cell level. Computational methods to process scRNA-seq have limited accessibility to bench scientists, as they require significant amount of bioinformatics skills. Researchers from the University of ...
Read More »Detecting Sources of Transcriptional Heterogeneity in Large-Scale RNA-Seq Data Sets
Gene expression levels are dynamic molecular phenotypes that respond to biological, environmental, and technical perturbations. Here, University of Washington researchers use a novel replicate classifier approach for discovering transcriptional signatures and apply it to the Genotype-Tissue Expression (GTEx) data set. ...
Read More »