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PLoS One. 2010 Jul 29;5(7):e11652. doi: 10.1371/journal.pone.0011652.

Occupancy modeling, maximum contig size probabilities and designing metagenomics experiments.

Author information

1
Biological Sciences Division, University of Chicago, Chicago, Illinois, United States of America. sstanhop@bsd.uchicago.edu

Abstract

Mathematical aspects of coverage and gaps in genome assembly have received substantial attention by bioinformaticians. Typical problems under consideration suppose that reads can be experimentally obtained from a single genome and that the number of reads will be set to cover a large percentage of that genome at a desired depth. In metagenomics experiments genomes from multiple species are simultaneously analyzed and obtaining large numbers of reads per genome is unlikely. We propose the probability of obtaining at least one contig of a desired minimum size from each novel genome in the pool without restriction based on depth of coverage as a metric for metagenomic experimental design. We derive an approximation to the distribution of maximum contig size for single genome assemblies using relatively few reads. This approximation is verified in simulation studies and applied to a number of different metagenomic experimental design problems, ranging in difficulty from detecting a single novel genome in a pool of known species to detecting each of a random number of novel genomes collectively sized and with abundances corresponding to given distributions in a single pool.

PMID:
20686599
PMCID:
PMC2912229
DOI:
10.1371/journal.pone.0011652
[Indexed for MEDLINE]
Free PMC Article

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