title: A two-stage statistical procedure for feature selection and comparison in functional analysis of metagenomes.
abstract: BACKGROUND
  With the advance of new sequencing technologies producing massive short reads data, metagenomics is rapidly growing, especially in the fields of environmental biology and medical science. The metagenomic data are not only high dimensional with large number of features and limited number of samples but also complex with a large number of zeros and skewed distribution. Efficient computational and statistical tools are needed to deal with these unique characteristics of metagenomic sequencing data. In metagenomic studies, one main objective is to assess whether and how multiple microbial communities differ under various environmental conditions.
  
  
  RESULTS
  We propose a two-stage statistical procedure for selecting informative features and identifying differentially abundant features between two or more groups of microbial communities. In the functional analysis of metagenomes, the features may refer to the pathways, subsystems, functional roles and so on. In the first stage of the proposed procedure, the informative features are selected using elastic net as reducing the dimension of metagenomic data. In the second stage, the differentially abundant features are detected using generalized linear models with a negative binomial distribution. Compared with other available methods, the proposed approach demonstrates better performance for most of the comprehensive simulation studies. The new method is also applied to two real metagenomic datasets related to human health. Our findings are consistent with those in previous reports.
  
  
  BACKGROUND
  R code and two example datasets are available at http://cals.arizona.edu/∼anling/software.htm.
  
  
  BACKGROUND
  Supplementary file is available at Bioinformatics online.
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Naruekamol
authors.initials: N
authors.lastname: Pookhao
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Michael B
authors.initials: MB
authors.lastname: Sohn
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Qike
authors.initials: Q
authors.lastname: Li
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Isaac
authors.initials: I
authors.lastname: Jenkins
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Ruofei
authors.initials: R
authors.lastname: Du
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Hongmei
authors.initials: H
authors.lastname: Jiang
authors.affiliation: Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA Department of Agricultural & Biosystems Engineering, Interdisciplinary Program in Statistics, University of Arizona, Tucson, AZ, 85721 and Department of Statistics, Northwestern University, Evanston, IL 60208, USA.
authors.forename: Lingling
authors.initials: L
authors.lastname: An
mesh_terms: D016022:Case-Control Studies; D003627:Data Interpretation, Statistical; D041981:Gastrointestinal Tract / Q000382:microbiology; D015964:Gene Expression Regulation, Bacterial; D005798:Genes, Bacterial / Q000235:genetics*; D006801:Humans; D015212:Inflammatory Bowel Diseases / Q000209:etiology*; D056186:Metagenomics / Q000379:methods*; D009093:Mucus / Q000382:microbiology; D009765:Obesity / Q000150:complications / Q000235:genetics*; D012372:ROC Curve; D012463:Saliva / Q000382:microbiology