Analysis of Poly(A) Site Choice Using a Java-Based Clustering Algorithm

  • Patrick E. Thomas
Part of the Methods in Molecular Biology book series (MIMB, volume 1255)


Modern high-throughput DNA sequencing has the potential to generate large volumes of data for analysis by investigators—including poly(A) site data. Here I describe a computational method to compare poly(A) site choice differences between two large data sets based on the relative abundance and position of tags within each reference sequence to which they are aligned. This method provides rapid quantification and visualization of differences and similarities in poly(A) site choice between the two datasets.

Key words

Alternative polyadenylation Java Next generation sequencing PAT-seq 



This work was supported by the National Science Foundation (award MCB-0313472 to Drs. Arthur G. Hunt and Q. Quinn Li, and an RET supplement to award IOS-0817818).


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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Plant and Soil SciencesUniversity of KentuckyLexingtonUSA
  2. 2.Franklin-Simpson High SchoolFranklinUSA

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