Tag Archives: transcriptional heterogeneity

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. ...

The rapid growth of single-cell RNA-seq studies (scRNA-seq) demands efficient data storage, processing, and analysis. Big-data technology provides a framework that facilitates the comprehensive discovery of biological signals from inter-institutional scRNA-seq datasets. There are several strategies to solve the stochastic ...

Single-cell transcriptomics provides us unprecedented opportunity to understand the transcriptional stochasticity and cellular heterogeneity in great detail, which are crucial for maintaining cell functions and for facilitating disease progression or treatment response. Such stochasticity and heterogeneity are always masked in ...

The transcriptional state of a cell reflects a variety of biological factors, from cell-type-specific features to transient processes such as the cell cycle, all of which may be of interest. However, identifying such aspects from noisy single-cell RNA-seq data remains ...

The significance of single cell transcription resides not only in the cumulative expression strength of the cell population but also in its heterogeneity. Researchers at the Baylor Institute for Immunology Research propose a new model that improves the detection of ...