Use of simulated data sets to evaluate the fidelity of metagenomic processing methods.
Metagenomics is a rapidly emerging field of research for studying microbial communities. To evaluate methods presently used to process metagenomic sequences, we constructed three simulated data sets of varying complexity by combining sequencing reads randomly selected from 113 isolate genomes. These data sets were designed to model real metagenomes in terms of complexity and phylogenetic composition. We assembled sampled reads using three commonly used genome assemblers (Phrap, Arachne and JAZZ), and predicted genes using two popular gene-finding pipelines (fgenesb and CRITICA/GLIMMER). The phylogenetic origins of the assembled contigs were predicted using one sequence similarity-based (blast hit distribution) and two sequence composition-based (PhyloPythia, oligonucleotide frequencies) binning methods. We explored the effects of the simulated community structure and method combinations on the fidelity of each processing step by comparison to the corresponding isolate genomes. The simulated data sets are available online to facilitate standardized benchmarking of tools for metagenomic analysis.
Mavromatis
Konstantinos
K
Department of Energy Joint Genome Institute (DOE-JGI), 2800 Mitchell Drive, Walnut Creek, California 94598, USA. kmavrommatis@lbl.gov
Ivanova
Natalia
N
Barry
Kerrie
K
Shapiro
Harris
H
Goltsman
Eugene
E
McHardy
Alice C
AC
Rigoutsos
Isidore
I
Salamov
Asaf
A
Korzeniewski
Frank
F
Land
Miriam
M
Lapidus
Alla
A
Grigoriev
Igor
I
Richardson
Paul
P
Hugenholtz
Philip
P
Kyrpides
Nikos C
NC
D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods* / Q000592:standards; D003198:Computer Simulation; D030541:Databases, Genetic; D016680:Genome, Bacterial / Q000235:genetics; D023281:Genomics / Q000379:methods* / Q000592:standards; D010802:Phylogeny; D012984:Software