title: Multivariate analysis of functional metagenomes.
abstract: Metagenomics is a primary tool for the description of microbial and viral communities. The sheer magnitude of the data generated in each metagenome makes identifying key differences in the function and taxonomy between communities difficult to elucidate. Here we discuss the application of seven different data mining and statistical analyses by comparing and contrasting the metabolic functions of 212 microbial metagenomes within and between 10 environments. Not all approaches are appropriate for all questions, and researchers should decide which approach addresses their questions. This work demonstrated the use of each approach: for example, random forests provided a robust and enlightening description of both the clustering of metagenomes and the metabolic processes that were important in separating microbial communities from different environments. All analyses identified that the presence of phage genes within the microbial community was a predictor of whether the microbial community was host-associated or free-living. Several analyses identified the subtle differences that occur with environments, such as those seen in different regions of the marine environment.
authors.affiliation: Department of Biology, San Diego State University San Diego, CA, USA.
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Dinsdale
authors.forename: Robert A
authors.initials: RA
authors.lastname: Edwards
authors.forename: Barbara A
authors.initials: BA
authors.lastname: Bailey
authors.forename: Imre
authors.initials: I
authors.lastname: Tuba
authors.forename: Sajia
authors.initials: S
authors.lastname: Akhter
authors.forename: Katelyn
authors.initials: K
authors.lastname: McNair
authors.forename: Robert
authors.initials: R
authors.lastname: Schmieder
authors.forename: Naneh
authors.initials: N
authors.lastname: Apkarian
authors.forename: Michelle
authors.initials: M
authors.lastname: Creek
authors.forename: Eric
authors.initials: E
authors.lastname: Guan
authors.forename: Mayra
authors.initials: M
authors.lastname: Hernandez
authors.forename: Katherine
authors.initials: K
authors.lastname: Isaacs
authors.forename: Chris
authors.initials: C
authors.lastname: Peterson
authors.forename: Todd
authors.initials: T
authors.lastname: Regh
authors.forename: Vadim
authors.initials: V
authors.lastname: Ponomarenko
keywords: canonical discriminant analysis; metagenomics; microbiology; principal component analysis; random forest; statistics