MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data
MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data
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DOI:
10.1093/bioinformatics/btt001
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发表时间:
2013-02-15
期刊:
影响因子:
5.8
通讯作者:
Perkins, Theodore J.
中科院分区:
文献类型:
--
作者:
Ramachandran, Parameswaran;Palidwor, Gareth A.;Perkins, Theodore J.
Results: In this article, we investigate the use of strand cross-correlation to estimate mean fragment length of single-end data and show that traditional estimation approaches have mixed reliability. We observe that the mappability of different parts of the genome can introduce an artificial bias into cross-correlation computations, resulting in incorrect fragment-length estimates. We propose a new approach, called mappability-sensitive cross-correlation (MaSC), which removes this bias and allows for accurate and reliable fragment-length estimation. We analyze the computational complexity of this approach, and evaluate its performance on a test suite of NGS datasets, demonstrating its superiority to traditional cross-correlation analysis.Availability: An open-source Perl implementation of our approach is available at ext-link-type="uri" xlink:href="http://www.perkinslab.ca/Software.html" xmlns:xlink="http://www.w3.org/1999/xlink">http://www.perkinslab.ca/Software.html.Contact: tperkins@ohri.caSupplementary information: ext-link-type="uri" xlink:href="http://bioinformatics.oxfordjournals.org/cgi/content/full/btt001/DC1" xmlns:xlink="http://www.w3.org/1999/xlink">Supplementary data are available at Bioinformatics online.