Metadata-Version: 2.1
Name: q2-dbbact
Version: 1.1.1
Summary: A qiime2 (https://qiime2.org/) plugin for dbBact (http://dbbact.org) annotations of microbiome experiments
Home-page: http://dbbact.org
Author: dbBact team
Author-email: info@dbbact.org
License: BSD
Description: # q2-dbbact
        A [Qiime2](https://qiime2.org/) plugin for [dbBact](http://dbbact.org)
        
        ![wordcloud](https://github.com/amnona/q2-dbbact/blob/main/pics/cfs-wordcloud.jpg)
        ![enriched barplot](https://github.com/amnona/q2-dbbact/blob/main/pics/enriched_terms.jpg)
        ![heatmap](https://github.com/amnona/q2-dbbact/blob/main/pics/heatmap.jpg)
         
        # Features:
        * Differential abundance testing using [Calour](https://github.com/biocore/calour) rank-mean differential abundance test (with [dsFDR](https://escholarship.org/content/qt3j68q5n7/qt3j68q5n7_noSplash_e7ad1cf405f67b9cef0e5a99c1804fd5.pdf) correction).
        * dbBact term enrichment from differntial abundance results of qiime2 (i.e. songbird/q2-aldex2/ancom/dacomp or the built in rank-mean test).
        * Create a wordcloud of dbBact terms for a given feature table.
        * Generate an interactive heatmap visualization for a feature table. The heatmap provides links to dbBact annotations for each ASV.
        * Generate Venn diagram for a differential abundance result and a given dbBact term.
        * Background dbBact term enrichment analysis for experiments without controls (i.e. what terms are enriched in the bacteria in a given feature table compared to all dbBact experiments of a given type).
        
        # Examples:
        ## Run the q2-dbBact enrichment pipeline for a given feature table:
        Our input is a feature table and a metadata file with a given column dividing our samples into two groups.
        
        q2-dbBact will detect ASVs different between the two groups, and identify dbBact terms enriched in one of the two groups compared to the other
        
        ``` qiime dbbact enrich-pipeline --i-table cfs-merged.qza --m-metadata-file map.cfs.txt --p-field Subject --output-dir cfs-pipeline```
        
        ## Draw an interactive heatmap
        This creates a zoomable heatmap with a list of dbBact annotation for each bacteria that is clicked. Useful for exploring your sequencing results and getting a feeling for what is going on (contaminations, bacterial sources, groups of samples, etc.)
        
        Our input is a feature table and a metadata file with a given column dividing our samples into two groups.
        
        ```qiime dbbact heatmap --i-table cfs-table.qza --i-repseqs cfs-rep-seqs.qza --i-taxonomy cfs-taxonomy.qza --m-metadata-file map.cfs.txt --p-sort-field Subject --o-visualization heatmap-cfs```
        
        ![heatmap](https://github.com/amnona/q2-dbbact/blob/main/pics/heatmap.jpg)
        
        ## Draw a dbBact terms wordcloud for the set of bacteria in a feature-table
        The wordcloud is created for all the bacteria in the feature table.
        
        The output wordcloud words are dbBact terms associated with the bacteria. The word size corresponds to the F-score (recall and precision) of the term. Blue terms are positively associated (i.e. appear in COMMON/DOMINANT/HIGHER IN annotations) where as red terms (preceeded by a "-") are negatively associated (i.e. appear in LOWER IN annotations).
        
        ```qiime dbbact draw-wordcloud-vis --i-data cfs-table.qza --i-repseqs cfs-rep-seqs.qza --o-visualization wordcloud-cfs```
        
        ![wordcloud](https://github.com/amnona/q2-dbbact/blob/main/pics/cfs-wordcloud.jpg)
        
        ## Identify differentially abundant bacteria between two sample groups
        q2-dbBact utilizes the non-parametric (permutation based) Calour diff_abundance() function. By default it uses a rank-mean test with dsFDR multiple hypothesis correction.
        
        The test can also be performed as a paired test using an additional metadata pair-field (permutations are performed only between samples sharing the same pair-field value).
        
        ```qiime dbbact diff-abundance --i-table cfs-merged.qza --m-metadata-file map.cfs.txt --p-field Subject --p-alpha 0.1 --p-val1 Patient --p-val2 Control --o-diff diff-cfs-dsfdr```
        
        ## Identify and plot enriched dbBact terms between two groups of bacteria
        Performed on the output of a differential-abundance test. q2-dbBact supports the following formats:
        * [songbird](https://github.com/biocore/songbird)
        * [ancom](https://github.com/qiime2/q2-composition)
        * [q2-aldex2](https://library.qiime2.org/plugins/q2-aldex2/24/)
        * dbBact diff-abundance
        * any tsv file
        
        This command identifies dbBact terms the are significantly more associated with bacteria from one group compared to the other
        
        ```qiime dbbact enrichment --i-diff diff-cfs-dsfdr.qza --p-source dsfdr --o-enriched enriched-cfs-dsfdr```
        
        The output can be visualized (and the complete table saved) using the visualization command:
        
        ```qiime dbbact plot-enrichment --i-enriched enriched-cfs-dsfdr.qza --o-visualization barplot-enriched-cfs-dsfdr --p-labels CFS Control```
        
        ![enriched barplot](https://github.com/amnona/q2-dbbact/blob/main/pics/enriched_terms.jpg)
        
        ## Venn diagram for examining term distribution in the two groups
        Input is the results of a differential abundance analysis (which provides two ASV groups - positive and negative effect size), and a dbBact term.
        
        The venn diagram shows how many of the ASVs in each group have the term, as well as how many total dbBact ASVs have the term associated.
        
        ```qiime dbbact venn --i-diff diff-cfs-dsfdr.qza --p-terms "small village" --p-source dsfdr --p-label1 Control --p-label2 CFS --o-visualization venn-cfs-human-village```
        
        ![venn](https://github.com/amnona/q2-dbbact/blob/main/pics/venn-cfs-village.png)
        
Keywords: microbiome qiime2 dbbact database analysis bioinformatics
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: BSD License
Classifier: Environment :: Plugins
Classifier: Topic :: Software Development :: Libraries :: Application Frameworks
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Operating System :: Unix
Classifier: Operating System :: POSIX
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Requires-Python: >=3.6
Description-Content-Type: text/markdown
