TY - JOUR
T1 - QIIME 2 Enables Comprehensive End-to-End Analysis of Diverse Microbiome Data and Comparative Studies with Publicly Available Data
AU - Estaki, Mehrbod
AU - Jiang, Lingjing
AU - Bokulich, Nicholas A.
AU - McDonald, Daniel
AU - González, Antonio
AU - Kosciolek, Tomasz
AU - Martino, Cameron
AU - Zhu, Qiyun
AU - Birmingham, Amanda
AU - Vázquez-Baeza, Yoshiki
AU - Dillon, Matthew R.
AU - Bolyen, Evan
AU - Caporaso, J. Gregory
AU - Knight, Rob
N1 - Publisher Copyright:
© 2020 The Authors.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses—e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://qiime2.org. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://forum.qiime2.org.
AB - QIIME 2 is a completely re-engineered microbiome bioinformatics platform based on the popular QIIME platform, which it has replaced. QIIME 2 facilitates comprehensive and fully reproducible microbiome data science, improving accessibility to diverse users by adding multiple user interfaces. QIIME 2 can be combined with Qiita, an open-source web-based platform, to re-use available data for meta-analysis. The following basic protocol describes how to install QIIME 2 on a single computer and analyze microbiome sequence data, from processing of raw DNA sequence reads through generating publishable interactive figures. These interactive figures allow readers of a study to interact with data with the same ease as its authors, advancing microbiome science transparency and reproducibility. We also show how plug-ins developed by the community to add analysis capabilities can be installed and used with QIIME 2, enhancing various aspects of microbiome analyses—e.g., improving taxonomic classification accuracy. Finally, we illustrate how users can perform meta-analyses combining different datasets using readily available public data through Qiita. In this tutorial, we analyze a subset of the Early Childhood Antibiotics and the Microbiome (ECAM) study, which tracked the microbiome composition and development of 43 infants in the United States from birth to 2 years of age, identifying microbiome associations with antibiotic exposure, delivery mode, and diet. For more information about QIIME 2, see https://qiime2.org. To troubleshoot or ask questions about QIIME 2 and microbiome analysis, join the active community at https://forum.qiime2.org.
KW - QIIME 2
KW - Qiita
KW - bioinformatics
KW - metagenomics
KW - microbiome
UR - http://www.scopus.com/inward/record.url?scp=85084107260&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85084107260&partnerID=8YFLogxK
U2 - 10.1002/cpbi.100
DO - 10.1002/cpbi.100
M3 - Article
C2 - 32343490
AN - SCOPUS:85084107260
SN - 1934-3396
VL - 70
JO - Current protocols in bioinformatics
JF - Current protocols in bioinformatics
IS - 1
M1 - e100
ER -