A Statistical Framework for the Functional Analysis of Metagenomes
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.
- Research Organization:
- Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
- Sponsoring Organization:
- Computational Research Division; Genomics Division
- DOE Contract Number:
- DE-AC02-05CH11231
- OSTI ID:
- 979916
- Report Number(s):
- LBNL-2871E; TRN: US201011%%468
- Journal Information:
- Lecture Notes in Computer Science, Vol. RECOMB, Issue 5541; Related Information: Journal Publication Date: 2009
- Country of Publication:
- United States
- Language:
- English
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