MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data | Zendy

Parameswaran Ramachandran | Zendy; Gareth Palidwor | Zendy; Christopher J. Porter | Zendy; Theodore J. Perkins | Zendy

Open Access

MaSC: mappability-sensitive cross-correlation for estimating mean fragment length of single-end short-read sequencing data

Author(s) -

Parameswaran Ramachandran,

Gareth Palidwor,

Christopher J. Porter,

Theodore J. Perkins

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/btt001

Subject(s) - fragment (logic) , computer science , perl , subroutine , cross correlation , algorithm , correlation , reliability (semiconductor) , software , data mining , statistics , mathematics , power (physics) , physics , geometry , quantum mechanics , world wide web , programming language , operating system

Reliable estimation of the mean fragment length for next-generation short-read sequencing data is an important step in next-generation sequencing analysis pipelines, most notably because of its impact on the accuracy of the enriched regions identified by peak-calling algorithms. Although many peak-calling algorithms include a fragment-length estimation subroutine, the problem has not been adequately solved, as demonstrated by the variability of the estimates returned by different algorithms.

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