title: Evaluation of subsampling-based normalization strategies for tagged high-throughput sequencing data sets from gut microbiomes.
abstract: Several subsampling-based normalization strategies were applied to different high-throughput sequencing data sets originating from human and murine gut environments. Their effects on the data sets' characteristics and normalization efficiencies, as measured by several β-diversity metrics, were compared. For both data sets, subsampling to the median rather than the minimum number appeared to improve the analysis.
authors: CSIRO Preventative Health National Research Flagship and Division of Livestock Industries, Queensland Bioscience Precinct, St. Lucia, QLD 4067, Australia.
authors: Daniel Aguirre de
authors: DA
authors: Cárcer
authors: Stuart E
authors: SE
authors: Denman
authors: Chris
authors: C
authors: McSweeney
authors: Mark
authors: M
authors: Morrison
mesh_terms: D000818:Animals; D041981:Gastrointestinal Tract / Q000382:microbiology*; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods / Q000592:standards; D006801:Humans; D054892:Metagenome; D056186:Metagenomics / Q000379:methods* / Q000592:standards*; D051379:Mice; D013048:Specimen Handling / Q000379:methods* / Q000592:standards*; D013223:Statistics as Topic