A statistical toolbox for metagenomics: assessing functional diversity in microbial communities.

BMC Bioinformatics
Patrick D Schloss, Jo Handelsman

Abstract

The 99% of bacteria in the environment that are recalcitrant to culturing have spurred the development of metagenomics, a culture-independent approach to sample and characterize microbial genomes. Massive datasets of metagenomic sequences have been accumulated, but analysis of these sequences has focused primarily on the descriptive comparison of the relative abundance of proteins that belong to specific functional categories. More robust statistical methods are needed to make inferences from metagenomic data. In this study, we developed and applied a suite of tools to describe and compare the richness, membership, and structure of microbial communities using peptide fragment sequences extracted from metagenomic sequence data. Application of these tools to acid mine drainage, soil, and whale fall metagenomic sequence collections revealed groups of peptide fragments with a relatively high abundance and no known function. When combined with analysis of 16S rRNA gene fragments from the same communities these tools enabled us to demonstrate that although there was no overlap in the types of 16S rRNA gene sequence observed, there was a core collection of operational protein families that was shared among the three environments. The ...Continue Reading

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Datasets Mentioned

BETA
AE017334
ATCC
10987

Software Mentioned

fastgenesb
greengenes
MG
SPADE
ARB
LIBSHUFF
AMOVA
BLAST
DOTUR
SONS

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