A new statistic for efficient detection of repetitive sequences | Zendy

Sijie Chen | Zendy; Yixin Chen | Zendy; Fengzhu Sun | Zendy; Michael S. Waterman | Zendy; Xuegong Zhang | Zendy

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A new statistic for efficient detection of repetitive sequences

Author(s) -

Sijie Chen,

Yixin Chen,

Fengzhu Sun,

Michael S. Waterman,

Xuegong Zhang

Publication year - 2019

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/btz262

Subject(s) - statistic , computer science , palindrome , mit license , data mining , computational biology , biology , license , genome , mathematics , genetics , statistics , gene , operating system

Detecting sequences containing repetitive regions is a basic bioinformatics task with many applications. Several methods have been developed for various types of repeat detection tasks. An efficient generic method for detecting most types of repetitive sequences is still desirable. Inspired by the excellent properties and successful applications of the D2 family of statistics in comparative analyses of genomic sequences, we developed a new statistic D2R that can efficiently discriminate sequences with or without repetitive regions.

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