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Title: A Statistical Framework for the Functional Analysis of Metagenomes

Abstract

Metagenomic studies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. They present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. They also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements. They tested their method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that their framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.

Authors:
; ; ;
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
Computational Research Division; Genomics Division
OSTI Identifier:
979916
Report Number(s):
LBNL-2871E
TRN: US201011%%468
DOE Contract Number:  
DE-AC02-05CH11231
Resource Type:
Journal Article
Journal Name:
Lecture Notes in Computer Science
Additional Journal Information:
Journal Volume: RECOMB; Journal Issue: 5541; Related Information: Journal Publication Date: 2009
Country of Publication:
United States
Language:
English
Subject:
97; ABUNDANCE; APPROXIMATIONS; FUNCTIONAL ANALYSIS; FUNCTIONALS; GENES; GENETICS; MICROORGANISMS; RELIABILITY; STATISTICS; metagenomics, functional analysis, function comparison, Lander-Waterman

Citation Formats

Sharon, Itai, Pati, Amrita, Markowitz, Victor, and Pinter, Ron Y. A Statistical Framework for the Functional Analysis of Metagenomes. United States: N. p., 2008. Web.
Sharon, Itai, Pati, Amrita, Markowitz, Victor, & Pinter, Ron Y. A Statistical Framework for the Functional Analysis of Metagenomes. United States.
Sharon, Itai, Pati, Amrita, Markowitz, Victor, and Pinter, Ron Y. Wed . "A Statistical Framework for the Functional Analysis of Metagenomes". United States. https://www.osti.gov/servlets/purl/979916.
@article{osti_979916,
title = {A Statistical Framework for the Functional Analysis of Metagenomes},
author = {Sharon, Itai and Pati, Amrita and Markowitz, Victor and Pinter, Ron Y},
abstractNote = {Metagenomic studies consider the genetic makeup of microbial communities as a whole, rather than their individual member organisms. The functional and metabolic potential of microbial communities can be analyzed by comparing the relative abundance of gene families in their collective genomic sequences (metagenome) under different conditions. Such comparisons require accurate estimation of gene family frequencies. They present a statistical framework for assessing these frequencies based on the Lander-Waterman theory developed originally for Whole Genome Shotgun (WGS) sequencing projects. They also provide a novel method for assessing the reliability of the estimations which can be used for removing seemingly unreliable measurements. They tested their method on a wide range of datasets, including simulated genomes and real WGS data from sequencing projects of whole genomes. Results suggest that their framework corrects inherent biases in accepted methods and provides a good approximation to the true statistics of gene families in WGS projects.},
doi = {},
journal = {Lecture Notes in Computer Science},
number = 5541,
volume = RECOMB,
place = {United States},
year = {2008},
month = {10}
}