Please cite the paper below for the cleanUpdTSeq package.

  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

A BibTeX entry for LaTeX users is

  @Article{,
    title = {Accurate identification of polyadenylation sites from 3' end deep 
sequencing using a naive Bayes classifier},
    author = {Sarah Sheppard and Nathan Lawson and Lihua Zhu},
    journal = {Bioinformatics},
    volume = {29},
    year = {2013},
    number = {20},
    pages = {2564},
    url = {http://bioinformatics.oxfordjournals.org/content/29/20/2564.long},
    doi = {10.1093/bioinformatics/btt446},
    pubmedid = {23962617},
    issn = {1460-2059},
    abstract = {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.},
  }