Exploring Microbial Diversity with QIIME2
Jialin Hu
Disclaimer
This guide is for educational purposes only. It does not
substitute professional advice, and users should consult experts for specific
concerns. The information provided may contain errors, and the authors disclaim
any liability for losses or damages arising from its use. Mention of specific
tools or software does not imply endorsement. Users should exercise discretion
and verify information independently. The guide may be subject to change
without notice. By using this guide, you agree to these terms
Abstract
This tutorial introduces Qiime2 for non-phylogenetic diversity
analysis, covering core metrics calculation, emphasizing standardized sampling
depth, and using pre-processed feature tables and metadata. It then explores
beta group significance analysis via qiime diversity beta-group-significance,
detailing parameters and introducing pairwise testing. The tutorial concludes
with a concise demonstration of PCoA plot creation using qiime emperor plot,
highlighting input requirements and insights into result interpretation. Users
are encouraged to explore the interactive Qiime2 visualization for valuable
insights into microbial community relationships and factors influencing
diversity. Overall, the tutorial serves as a brief yet comprehensive
introduction to Qiime2 for enhanced capabilities in microbiome research.
Steps
Title
Title: Exploring Microbial Diversity with QIIME 2
What is qiime2?
Qiime2 (Quantitative Insights Into Microbial Ecology 2) is a
powerful bioinformatics platform designed for the analysis of microbial
communities, particularly from high-throughput sequencing data. Developed by
the Knight Lab, Qiime2 provides a comprehensive suite of tools for processing,
analyzing, and visualizing microbiome data. It is an open-source and extensible
software that facilitates reproducible and transparent microbiome research.
Install Qiime2
Install Qiime2 in your Conda
environment. If you are using a MacBook, you can follow the installation
instructions provided on the Qiime2 website. For Windows, consider using a
virtual box with a Linux distribution to run Qiime2.
Set Working Directory
Navigate to the directory where
your metadata file and feature table are located using the cd command. This
directory should contain the pre-processed feature table, excluding chimeras
and singletons.
Perform Core Metrics for Non-phylogenetic Diversity Analysis
Use the qiime diversity
core-metrics command to calculate diversity metrics. Perform Core Metrics for
Non-phylogenetic Diversity Analysis using this command
qiime diversity core-metrics \ --i-table seq-nochim-biom-table-nosingleton-filtered.qza \ --p-sampling-depth 12504 \ --m-metadata-file metadata_fungi.tsv \ --output-dir core-metrics-results \ --verbose (Customize the command by replacing the input and metadata file names. Choose an appropriate sampling depth based on rarefaction curves and feature table summaries.)
Perform Beta Group Significance Analysis
Use the qiime diversity beta-group-significance command to assess the significance of group differences. qiime diversity beta-group-significance --i-distance-matrix bray_curtis_distance_matrix.qza/--m-metadata-file metadata_fungi.tsv /
--m-metadata-column Source/
--o-visualization bray-curtis-source-sig.qzv /
--p-pairwise/
(Customize the command with your distance matrix file, metadata
file, and the column in the metadata file you want to analyze. Consider adding
the --p-pairwise option for pairwise comparisons.)
Make a PCoA Plot
Generate a PCoA plot using the qiime emperor plot command.
qiime emperror plot
-–i-pcoa bray_curtis_pcoa_results.qza
--m-metadata-file metadata_fungi.tsv
--o-visualization bray_curtis_pcoa_emperor.qzv
(You can use other distance matrices like Jaccard. Customize the command with your
specific PCoA results file and metadata file.plot)
