Thresher: an improved algorithm for peak height thresholding of microbial community profiles | Zendy

V. Starke | Zendy; A. Steele | Zendy

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Thresher: an improved algorithm for peak height thresholding of microbial community profiles

Author(s) -

V. Starke,

A. Steele

Publication year - 2014

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/btu528

Subject(s) - replicate , thresholding , sample (material) , outlier , computer science , similarity (geometry) , software , statistics , species richness , pattern recognition (psychology) , algorithm , artificial intelligence , data mining , mathematics , biology , image (mathematics) , ecology , chemistry , chromatography , programming language

This article presents Thresher, an improved technique for finding peak height thresholds for automated rRNA intergenic spacer analysis (ARISA) profiles. We argue that thresholds must be sample dependent, taking community richness into account. In most previous fragment analyses, a common threshold is applied to all samples simultaneously, ignoring richness variations among samples and thereby compromising cross-sample comparison. Our technique solves this problem, and at the same time provides a robust method for outlier rejection, selecting for removal any replicate pairs that are not valid replicates.

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