z-logo
open-access-imgOpen Access
Accurate identification of polyadenylation sites from 3′ end deep sequencing using a naïve Bayes classifier
Author(s) -
Sarah E. Sheppard,
Nathan D. Lawson,
Lihua Julie Zhu
Publication year - 2013
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btt446
Subject(s) - polyadenylation , classifier (uml) , computational biology , bayes' theorem , computer science , artificial intelligence , identification (biology) , biology , pattern recognition (psychology) , genetics , gene , bayesian probability , gene expression , botany
3' end processing is important for transcription termination, mRNA stability and regulation of gene expression. To identify 3' ends, most techniques use an oligo-dT primer to construct deep sequencing libraries. However, this approach can lead to identification of artifactual polyadenylation sites due to internal priming in homopolymeric stretches of adenines. Although heuristic filters have been applied in these cases, they typically result in a high proportion of both false-positive and -negative classifications. Therefore, there is a need to develop improved algorithms to better identify mis-priming events in oligo-dT primed sequences.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom