METAGENassist
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Application data |
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| Biological application domain(s) | Metagenomics, Machine learning |
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| Principal bioinformatics method(s) | Visualisation, Statistical calculation, Sequence clustering |
| Created at | University of Alberta |
| Maintained? | Yes |
| Input format(s) | mothur, QIIME, MG-RAST, MEGAN, STAMP, Phoenix 2, CSV |
| Output format(s) | PNG, PDF, CSV |
| Software features | Easy-to-use point-and-click web interface; data visualization; publication-quality graphs and charts; wide variety of statistical methods; taxon-to-phenotype mapping; data filtering and normalization; supports many common input formats |
Summary: User-friendly, web-based analytical pipeline for comparative metagenomic studies. Input can be derived from either 16S rRNA data or NextGen shotgun sequencing.
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Contents
Description
METAGENassist allows users to compare metagenomic samples using a variety of statistical methods via an easy-to-use web interface.
Data input formats
Researchers make their initial taxonomic assignments in other programs and then upload the resulting analysis file(s) to METAGENassist. Files from commonly used programs including mothur, QIIME, MEGAN, MG-RAST and STAMP can be read directly, or a taxonomic profile can be input in a generic Comma Separated Value (CSV) format. Data deriving from either 16S rRNA experiments or shotgun metagenomic sequencing can be used.
Data processing
Users a guided through data processing steps that include data integrity/quality checks, data filtering and normalization, and automated taxonomic-to-phenotypic mapping.
Statistical analysis
METAGENassist offers a wide array of commonly used statistical and machine learning methods including:
- univariate statistics - fold change analysis, t-tests, volcano plots, one-way ANOVA, correlation analysis;
- multivariate statistics - principal component analysis (PCA) and partial least squares - discriminant analysis (PLS-DA);
- clustering - dendrograms, heatmaps, K-means clustering, self organizing feature maps (SOM);
- supervised classification - random forests and support vector machine (SVM).
Data output
Upon completion, METAGENassist generates a variety of well-annotated tables and colorful, labeled graphs in an anti-aliased PNG format. PDF versions for some plots are also available. The processed data and images are available for download.
Links
References
To add a reference for METAGENassist, enter the PubMed ID in the field below and click 'Add'.
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