ESPRIT: Estimating species richness using large collections of 16S rRNA pyrosequences

Yijun Sun, Yunpeng Cai, Li Liu, Fahong Yu, Michael L. Farrell, William Mckendree, William Farmerie

Research output: Contribution to journalArticle

207 Scopus citations

Abstract

Recent metagenomics studies of environmental samples suggested that microbial communities are much more diverse than previously reported, and deep sequencing will significantly increase the estimate of total species diversity. Massively parallel pyrosequencing technology enables ultra-deep sequencing of complex microbial populations rapidly and inexpensively. However, computational methods for analyzing large collections of 16S ribosomal sequences are limited. We proposed a new algorithm, referred to as ESPRIT, which addresses several computational issues with prior methods. We developed two versions of ESPRIT, one for personal computers (PCs) and one for computer clusters (CCs). The PC version is used for small- and medium-scale data sets and can process several tens of thousands of sequences within a few minutes, while the CC version is for large-scale problems and is able to analyze several hundreds of thousands of reads within one day. Large-scale experiments are presented that clearly demonstrate the effectiveness of the newly proposed algorithm. The source code and user guide are freely available at http://www.biotech.ufl.edu/people/sun/esprit.html.

Original languageEnglish (US)
Article numbere76
JournalNucleic acids research
Volume37
Issue number10
DOIs
StatePublished - 2009

ASJC Scopus subject areas

  • Genetics

Fingerprint Dive into the research topics of 'ESPRIT: Estimating species richness using large collections of 16S rRNA pyrosequences'. Together they form a unique fingerprint.

  • Cite this