Accurate identification of polyadenylation sites from 3' end deep sequencing using a naive Bayes classifier
Program in Gene Function and Expression; Program in Molecular Medicine
Bioinformatics | Computational Biology
MOTIVATION: 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.
RESULTS: By analyzing sequence features flanking 3' ends derived from oligo-dT-based sequencing, we developed a naive Bayes classifier to classify them as true or false/internally primed. The resulting algorithm is highly accurate, outperforms previous heuristic filters and facilitates identification of novel polyadenylation sites.
SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
DOI of Published Version
Sheppard S, Lawson ND, Zhu LJ. Accurate identification of polyadenylation sites from 3' end deep sequencing using a naive Bayes classifier. Bioinformatics. 2013 Oct 15;29(20):2564-71. doi:10.1093/bioinformatics/btt446. Link to article on publisher's site
Bioinformatics (Oxford, England)
Sheppard SE, Lawson ND, Zhu LJ. (2013). Accurate identification of polyadenylation sites from 3' end deep sequencing using a naive Bayes classifier. Program in Gene Function and Expression Publications. https://doi.org/10.1093/bioinformatics/btt446. Retrieved from https://escholarship.umassmed.edu/pgfe_pp/229