RTK: efficient rarefaction analysis of large datasets | Zendy

Paul Saary | Zendy; Sofia K. Forslund | Zendy; Peer Bork | Zendy; Falk Hildebrand | Zendy

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RTK: efficient rarefaction analysis of large datasets

Author(s) -

Paul Saary,

Sofia K. Forslund,

Peer Bork,

Falk Hildebrand

Publication year - 2017

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/btx206

Subject(s) - rarefaction (ecology) , computer science , software , species evenness , source code , field (mathematics) , visualization , code (set theory) , count data , r package , data mining , computational science , species richness , programming language , statistics , mathematics , ecology , biology , set (abstract data type) , pure mathematics , poisson distribution

The rapidly expanding microbiomics field is generating increasingly larger datasets, characterizing the microbiota in diverse environments. Although classical numerical ecology methods provide a robust statistical framework for their analysis, software currently available is inadequate for large datasets and some computationally intensive tasks, like rarefaction and associated analysis.

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