QIIME 2 Core concepts

https://docs.qiime2.org/2023.5/concepts/#

Core concepts — QIIME 2 2023.5.1 documentation

Data files: QIIME 2 artifacts

Data produced by QIMME 2 exist as QIIME 2 artifacts.

A QIIME 2 artifact contains data and metadata.

The metadata describes things about the data, such as its type, format and how it was generated (provenance).

A QIIME 2 artifact typically has the .qza file extension when stored in a file.

 

Since QIIME 2 works with artifacts instead of data files (e.g. FASTA files),

you must create a QIIME 2 artifact by importing data.

You can import data at any step in an analysis, though typically you will start by importing raw sequence data.

QIIME 2 also has tools to export data from an artifact.

 

By using QIIME 2 artifacts instead of simple data files, QIIME 2 can automatically track the type, format, and provenance of data for researchers. Using artifacts instead of data files enables researchers to focus on the analyses they want to perform, instead of the particular format the data needs to be in for an analysis.

 

Artifacts enable QIIME 2 to track, in addition to the data itself, the provenance of how the data came to be.

With an artifact's provenance, you can trace back to all previous analyses that were run to produce the artifact,
including the input data used at each step.

This automatic, integrated, and decentralized provenance tracking of data enables a researcher to archive artifacts, or for example, send an artifact to a collaborator, with the ability to understand exactly how the artifact was created.

This enables replicability(복제가능성) and reproducibility(재현성) of analyses, as well as generation of diagrams and text that can be used in the methods section of a paper.

Provenance also supports and encourages the paper attribution to underlying tools (e.g. FastTree to build a phylogenetic(계통 발생의) tree) used to generate the artifact.

 

Data files: Visualizations

Visualizations are another type of data generated by QIIME 2.

When written to disk, visualization files typically have the .qzv file extension.

Visualzations contain similar types of metadata as QIIME 2 artifacts, including provenance information.

Similar to QIIME 2 artifacts, visualizations are standalone information that can be archived or shared with collarborators.

 

In contrast to QIIME 2 artifacts, visualizations are terminal outputs of an analysis, and can represent, for example, a statistical results table, an interactive visualization, static images, or really any combination of visual data representations.

Since visualizations are terminal outputs, they cannot be used as input other analyses in QIIME 2.

 

Tip
Use https://view.qiime2.org to easily view QIIME 2 artifacts and visualizations files (generally .qza and .qzv files) without requiring a QIIME installation. This is helpful for sharing QIIME 2 data with collarborators who may not have QIIME 2 installed. https://view.qiime2.org also supports viewing data provenance.

 

Semantic types

Every artifact generated by QIIME 2 has a semantic type associated with it.

Semantic types enable QIIME 2 to identify artifacts that are suitable inputs to an analysis.

For example, if an analysis expects a distance matrix as input,
QIIME 2 can determine which artifacts have a distance matrix semantic type
and prevent incompatible artifacts from being used in the analysis
(e.g. an artifact representing a phylogenetic tree).

 

Semantic types also help users avoid semantically incorrect analyses.

For example, a feature table could contain presence/absence data
(i.e., a 1 to indicate that an OTU was observed at least one time in a given sample,
and a 0 to indicate that an OTU was not observed at least one time in a given sample).

However, if that feature table were provided to an analysis computing a quantitative diversity metric
where OTU abundances are included in the calculation (e.g., weighted UniFrac),
the analysis would complete successfully, but the result would not be meaningful.

 

Check out the semantic types page for more information about semantic types and what types are currently available.

 

Plugins

QIIME 2 microbiome(미생물) analyses are made available to users via plugins.

To perform analyses with QIIME 2, you will install one or more plugins
that provide the specific analyses you are interested in.

For example, if you want to demultiplex your raw sequence data, you might use the q2-demux QIIME 2 plugin,
or if you're wanting to perform alpha- or beta-deversity analyses, you could use the q2-diversity plugin.

 

Plugins are software packages that can be developed by anyone.

The QIIME 2 team has developed several plugins for an initial end-to-end microbiome analysis pipline,
but third-party developers are encouraged to create their own plugins to provide additional analyses.

Third-party developers will define these plugins in the same way that the QIIME 2 team has define the "official" plugins.

This decentralized development of microbiome analysis functionality means
that many more analyses and tools will be accessible to QIIME 2 users, including the latest techniques and protocols.

Plugins also allow users to choose and customize analysis pipeline for their specific needs.

 

Check out the plugin availability page to see what plugins are currently available
and the future plugins page for those that are being developed.

 

Methods and Visualizers

QIIME 2 plugins define methods and visualizers that are used to perform analyses.

 

A method accepts some combination of QIIME 2 artifacts and parameters as input,
and produces one or more QIIME 2 artifacts as output.

These output artifacts could subsequently be used as input to other QIIME 2 methods or visualizers.

Methods can produce intermediate or terminal outputs in a QIIME 2 analysis.

For example, the rarefy method defined in the q2-feature-table plugin
accepts a feature table artifact and sampling depth as input
and produces a rarefied feature table artifact as output.

This rarefied feature table artifact could then be used in another analysis,
such as alpha diversity calculations provided by the alpha method in q2-diversity.

 

A visualizer is similar to a mehtod in that it accepts some combination of QIIME 2 artifacts and parameters as input.

In contrast to a method, a visualizer produces exactly one visualization as output.

Visualizations, by definition, cannot be used as input to other QIIME 2 methods or visualizers.

Thus, visualizers can only produce terminal output in a QIIME 2 analysis.