RNA editing generates cellular subsets with diverse sequence within populations
Dewi Harjanto, Theodore Papamarkou, Chris J. Oates and 3 more
Nature Communications · 2016
doi:10.1038/ncomms12145 (opens in a new tab)
We email you when a new notice or a question about this paper appears.
Abstract
RNA editing rate detected from bulk RNA-seq data can vary widely. Here, by constructing a hierarchical Bayesian model, the authors report substantial variance in editing signatures detected by RNA-seq data from both single cells and a cognate bulk sample.
Abstract licence: CC BY-NC-ND
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.