Digitaldlsorter: Deep-Learning on scRNA-Seq to Deconvolute Gene Expression Data.
Ontology highlight
ABSTRACT: The development of single cell transcriptome sequencing has allowed researchers the possibility to dig inside the role of the individual cell types in a plethora of disease scenarios. It also expands to the whole transcriptome what before was only possible for a few tenths of antibodies in cell population analysis. More importantly, it allows resolving the permanent question of whether the changes observed in a particular bulk experiment are a consequence of changes in cell type proportions or an aberrant behavior of a particular cell type. However, single cell experiments are still complex to perform and expensive to sequence making bulk RNA-Seq experiments yet more common. scRNA-Seq data is proving highly relevant information for the characterization of the immune cell repertoire in diff
SUBMITTER: Torroja C
PROVIDER: S-EPMC6824295 | biostudies-literature | 2019
REPOSITORIES: biostudies-literature
ACCESS DATA