dev-bump: 2023.7 (#556)

source/data-resources.rst

@@ -10,8 +10,8 @@ Taxonomy classifiers for use with q2-feature-classifier
 
 Naive Bayes classifiers trained on:
 
-- `Silva 138 99% OTUs full-length sequences <https://data.qiime2.org/2023.5/common/silva-138-99-nb-classifier.qza>`_ (MD5: ``b8609f23e9b17bd4a1321a8971303310``)
-- `Silva 138 99% OTUs from 515F/806R region of sequences <https://data.qiime2.org/2023.5/common/silva-138-99-515-806-nb-classifier.qza>`_ (MD5: ``e05afad0fe87542704be96ff483824d4``)
+- `Silva 138 99% OTUs full-length sequences <https://data.qiime2.org/2023.7/common/silva-138-99-nb-classifier.qza>`_ (MD5: ``b8609f23e9b17bd4a1321a8971303310``)
+- `Silva 138 99% OTUs from 515F/806R region of sequences <https://data.qiime2.org/2023.7/common/silva-138-99-515-806-nb-classifier.qza>`_ (MD5: ``e05afad0fe87542704be96ff483824d4``)
 - `Greengenes2 2022.10 full length sequences <https://data.qiime2.org/classifiers/greengenes/gg_2022_10_backbone_full_length.nb.qza>`_ (MD5: ``98d34227fe67b34f62b464466cca4ffa``)
 - `Greengenes2 2022.10 from 515F/806R region of sequences <https://data.qiime2.org/classifiers/greengenes/gg_2022_10_backbone.v4.nb.qza>`_ (MD5: ``43de361005ae6dcae61b078c0c835021``)
 
@@ -40,9 +40,9 @@ Weighted Taxonomic Classifiers
 
 These 16S rRNA gene classifiers were trained with weights that take into account the fact that not all species are equally likely to be observed. If your sample comes from any of the 14 habitat types we tested, these weighted classifiers should give you superior classification precision. If your sample doesn't come from one of those habitats, they might still help. If you have the time, training with weights specific to your habitat should help even more. Weights for a range of habitats `are available here <https://github.com/BenKaehler/readytowear>`_.
 
-- `Weighted Silva 138 99% OTUs full-length sequences <https://data.qiime2.org/2023.5/common/silva-138-99-nb-weighted-classifier.qza>`_ (MD5: ``48965bb0a9e63c411452a460d92cfc04``)
-- `Weighted Greengenes 13_8 99% OTUs full-length sequences <https://data.qiime2.org/2023.5/common/gg-13-8-99-nb-weighted-classifier.qza>`_ (MD5: ``2baf87fce174c5f6c22a4c4086b1f1fe``)
-- `Weighted Greengenes 13_8 99% OTUs from 515F/806R region of sequences <https://data.qiime2.org/2023.5/common/gg-13-8-99-515-806-nb-weighted-classifier.qza>`_ (MD5: ``8fb808c4af1c7526a2bdfaafa764e21f``)
+- `Weighted Silva 138 99% OTUs full-length sequences <https://data.qiime2.org/2023.7/common/silva-138-99-nb-weighted-classifier.qza>`_ (MD5: ``48965bb0a9e63c411452a460d92cfc04``)
+- `Weighted Greengenes 13_8 99% OTUs full-length sequences <https://data.qiime2.org/2023.7/common/gg-13-8-99-nb-weighted-classifier.qza>`_ (MD5: ``2baf87fce174c5f6c22a4c4086b1f1fe``)
+- `Weighted Greengenes 13_8 99% OTUs from 515F/806R region of sequences <https://data.qiime2.org/2023.7/common/gg-13-8-99-515-806-nb-weighted-classifier.qza>`_ (MD5: ``8fb808c4af1c7526a2bdfaafa764e21f``)
 
 Please cite the following reference, in addition to those listed above, if you use any of these weighted pre-trained classifiers:
 
@@ -77,10 +77,10 @@ QIIME-compatible SILVA releases (up to release 132), as well as the licensing in
 
 We also provide pre-formatted SILVA reference sequence and taxonomy files here that were processed using `RESCRIPt <https://github.com/bokulich-lab/RESCRIPt>`_. See licensing information below if you use these files.
 
-- `Silva 138 SSURef NR99 full-length sequences <https://data.qiime2.org/2023.5/common/silva-138-99-seqs.qza>`_ (MD5: ``de8886bb2c059b1e8752255d271f3010``)
-- `Silva 138 SSURef NR99 full-length taxonomy <https://data.qiime2.org/2023.5/common/silva-138-99-tax.qza>`_ (MD5: ``f12d5b78bf4b1519721fe52803581c3d``)
-- `Silva 138 SSURef NR99 515F/806R region sequences <https://data.qiime2.org/2023.5/common/silva-138-99-seqs-515-806.qza>`_ (MD5: ``a914837bc3f8964b156a9653e2420d22``)
-- `Silva 138 SSURef NR99 515F/806R region taxonomy <https://data.qiime2.org/2023.5/common/silva-138-99-tax-515-806.qza>`_ (MD5: ``e2c40ae4c60cbf75e24312bb24652f2c``)
+- `Silva 138 SSURef NR99 full-length sequences <https://data.qiime2.org/2023.7/common/silva-138-99-seqs.qza>`_ (MD5: ``de8886bb2c059b1e8752255d271f3010``)
+- `Silva 138 SSURef NR99 full-length taxonomy <https://data.qiime2.org/2023.7/common/silva-138-99-tax.qza>`_ (MD5: ``f12d5b78bf4b1519721fe52803581c3d``)
+- `Silva 138 SSURef NR99 515F/806R region sequences <https://data.qiime2.org/2023.7/common/silva-138-99-seqs-515-806.qza>`_ (MD5: ``a914837bc3f8964b156a9653e2420d22``)
+- `Silva 138 SSURef NR99 515F/806R region taxonomy <https://data.qiime2.org/2023.7/common/silva-138-99-tax-515-806.qza>`_ (MD5: ``e2c40ae4c60cbf75e24312bb24652f2c``)
 
 
 Please cite the following references if you use any of these pre-formatted files:
@@ -123,5 +123,5 @@ The following databases are intended for use with q2-fragment-insertion, and
 are constructed directly from the
 `SEPP-Refs project <https://github.com/smirarab/sepp-refs/>`_.
 
-- `Silva 128 SEPP reference database <https://data.qiime2.org/2023.5/common/sepp-refs-silva-128.qza>`_ (MD5: ``7879792a6f42c5325531de9866f5c4de``)
-- `Greengenes 13_8 SEPP reference database <https://data.qiime2.org/2023.5/common/sepp-refs-gg-13-8.qza>`_ (MD5: ``9ed215415b52c362e25cb0a8a46e1076``)
+- `Silva 128 SEPP reference database <https://data.qiime2.org/2023.7/common/sepp-refs-silva-128.qza>`_ (MD5: ``7879792a6f42c5325531de9866f5c4de``)
+- `Greengenes 13_8 SEPP reference database <https://data.qiime2.org/2023.7/common/sepp-refs-gg-13-8.qza>`_ (MD5: ``9ed215415b52c362e25cb0a8a46e1076``)

source/install/index.rst

@@ -38,10 +38,10 @@ option for all cases. In general we recommend the following:
 
 .. _core-distribution:
 
-QIIME 2 Core 2023.5 distribution
+QIIME 2 Core 2023.7 distribution
 ---------------------------------
 
-The QIIME 2 Core 2023.5 distribution includes the QIIME 2 framework, ``q2cli`` (a QIIME 2 command-line interface) and the following plugins:
+The QIIME 2 Core 2023.7 distribution includes the QIIME 2 framework, ``q2cli`` (a QIIME 2 command-line interface) and the following plugins:
 
 - ``q2-alignment``
 - ``q2-composition``
@@ -66,7 +66,7 @@ The QIIME 2 Core 2023.5 distribution includes the QIIME 2 framework, ``q2cli`` (
 - ``q2-types``
 - ``q2-vsearch``
 
-.. note:: The QIIME 2 Core 2023.5 distribution includes plugins and interfaces that are developed, maintained, tested, and distributed by the QIIME 2 development team. The Core distribution is necessary to run the commands in the :doc:`QIIME 2 tutorials <../tutorials/index>`. If there are additional QIIME 2 plugins or interfaces you would like to install, please consult the relevant package(s) documentation. Other types of distributions may be made available in the future in addition to Core.
+.. note:: The QIIME 2 Core 2023.7 distribution includes plugins and interfaces that are developed, maintained, tested, and distributed by the QIIME 2 development team. The Core distribution is necessary to run the commands in the :doc:`QIIME 2 tutorials <../tutorials/index>`. If there are additional QIIME 2 plugins or interfaces you would like to install, please consult the relevant package(s) documentation. Other types of distributions may be made available in the future in addition to Core.
 
 .. _macOS: https://www.apple.com/macos/
 .. _Windows: https://www.microsoft.com/en-us/windows

source/install/native.rst

@@ -42,13 +42,13 @@ Install QIIME 2 within a ``conda`` environment
 ----------------------------------------------
 
 Once you have Miniconda installed, create a ``conda`` environment and install
-the QIIME 2 Core 2023.5 distribution within the environment. We **highly**
+the QIIME 2 Core 2023.7 distribution within the environment. We **highly**
 recommend creating a *new* environment specifically for the QIIME 2 release
 being installed, as there are many required dependencies that you may not
 want added to an existing environment. You can choose whatever name you'd
 like for the environment. In this example, we'll name the environment
-``qiime2-2023.5`` to indicate what QIIME 2 release is installed (i.e.
-``2023.5``).
+``qiime2-2023.7`` to indicate what QIIME 2 release is installed (i.e.
+``2023.7``).
 
 
 .. raw:: html
@@ -68,32 +68,32 @@ like for the environment. In this example, we'll name the environment
             </p>
          </div>
          <div id="macOS-intel" class="tab-pane fade">
-            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.5-py38-osx-conda.yml
-   conda env create -n qiime2-2023.5 --file qiime2-2023.5-py38-osx-conda.yml</pre>
+            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.7-py38-osx-conda.yml
+   conda env create -n qiime2-2023.7 --file qiime2-2023.7-py38-osx-conda.yml</pre>
    <span>OPTIONAL CLEANUP</span>
-   <pre>rm qiime2-2023.5-py38-osx-conda.yml</pre>
+   <pre>rm qiime2-2023.7-py38-osx-conda.yml</pre>
          </div>
          <div id="macOS-apple-silicon" class="tab-pane fade">
             <p>These instructions are for users with <a href="https://support.apple.com/en-us/HT211814">Apple Silicon</a> chips (M1, M2, etc), and configures the installation of QIIME 2 in <a href="https://developer.apple.com/documentation/apple-silicon/about-the-rosetta-translation-environment">Rosetta 2 emulation mode</a>.</p>
-            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.5-py38-osx-conda.yml
-   CONDA_SUBDIR=osx-64 conda env create -n qiime2-2023.5 --file qiime2-2023.5-py38-osx-conda.yml
-   conda activate qiime2-2023.5
+            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.7-py38-osx-conda.yml
+   CONDA_SUBDIR=osx-64 conda env create -n qiime2-2023.7 --file qiime2-2023.7-py38-osx-conda.yml
+   conda activate qiime2-2023.7
    conda config --env --set subdir osx-64</pre>
    <span>OPTIONAL CLEANUP</span>
-   <pre>rm qiime2-2023.5-py38-osx-conda.yml</pre>
+   <pre>rm qiime2-2023.7-py38-osx-conda.yml</pre>
          </div>
          <div id="linux" class="tab-pane fade">
-            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.5-py38-linux-conda.yml
-   conda env create -n qiime2-2023.5 --file qiime2-2023.5-py38-linux-conda.yml</pre>
+            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.7-py38-linux-conda.yml
+   conda env create -n qiime2-2023.7 --file qiime2-2023.7-py38-linux-conda.yml</pre>
    <span>OPTIONAL CLEANUP</span>
-   <pre>rm qiime2-2023.5-py38-linux-conda.yml</pre>
+   <pre>rm qiime2-2023.7-py38-linux-conda.yml</pre>
          </div>
          <div id="wsl" class="tab-pane fade">
             <p>These instructions are identical to the Linux instructions and are intended for users of the <a href="https://learn.microsoft.com/en-us/windows/wsl/about">Windows Subsystem for Linux</a>.</p>
-            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.5-py38-linux-conda.yml
-   conda env create -n qiime2-2023.5 --file qiime2-2023.5-py38-linux-conda.yml</pre>
+            <pre>wget https://data.qiime2.org/distro/core/qiime2-2023.7-py38-linux-conda.yml
+   conda env create -n qiime2-2023.7 --file qiime2-2023.7-py38-linux-conda.yml</pre>
    <span>OPTIONAL CLEANUP</span>
-   <pre>rm qiime2-2023.5-py38-linux-conda.yml</pre>
+   <pre>rm qiime2-2023.7-py38-linux-conda.yml</pre>
          </div>
       </div>
    </div>
@@ -107,7 +107,7 @@ Now that you have a QIIME 2 environment, activate it using the environment's nam
 .. command-block::
    :no-exec:
 
-   conda activate qiime2-2023.5
+   conda activate qiime2-2023.7
 
 To deactivate an environment, run ``conda deactivate``.
 
@@ -146,13 +146,13 @@ of QIIME 2 and one with the newer version.
 -----------------------
 
 If at any point during the analysis the QIIME 2 conda environment is closed
-or deactivated, QIIME 2 2023.5 can be activated (or reactivated) by running
+or deactivated, QIIME 2 2023.7 can be activated (or reactivated) by running
 the following command:
 
 .. command-block::
    :no-exec:
 
-   conda activate qiime2-2023.5
+   conda activate qiime2-2023.7
 
 To determine the currently active conda environment, run the following
 command and look for the line that starts with "active environment":

source/install/virtual/docker.rst

@@ -14,7 +14,7 @@ In a terminal with Docker activated, run:
 .. command-block::
    :no-exec:
 
-   docker pull quay.io/qiime2/core:2023.5
+   docker pull quay.io/qiime2/core:2023.7
 
 3. Confirm the installation
 ---------------------------
@@ -24,4 +24,4 @@ Run the following to confirm that the image was successfully fetched.
 .. command-block::
    :no-exec:
 
-   docker run -t -i -v $(pwd):/data quay.io/qiime2/core:2023.5 qiime
+   docker run -t -i -v $(pwd):/data quay.io/qiime2/core:2023.7 qiime

source/tutorials/atacama-soils.rst

@@ -45,7 +45,7 @@ available as a Google Sheet. This ``sample-metadata.tsv`` file is used
 throughout the rest of the tutorial.
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/atacama-soils/sample_metadata.tsv
+   :url: https://data.qiime2.org/2023.7/tutorials/atacama-soils/sample_metadata.tsv
    :saveas: sample-metadata.tsv
 
 
@@ -61,15 +61,15 @@ tutorial to further improve the run time.
    mkdir emp-paired-end-sequences
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/atacama-soils/10p/forward.fastq.gz
+   :url: https://data.qiime2.org/2023.7/tutorials/atacama-soils/10p/forward.fastq.gz
    :saveas: emp-paired-end-sequences/forward.fastq.gz
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/atacama-soils/10p/reverse.fastq.gz
+   :url: https://data.qiime2.org/2023.7/tutorials/atacama-soils/10p/reverse.fastq.gz
    :saveas: emp-paired-end-sequences/reverse.fastq.gz
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/atacama-soils/10p/barcodes.fastq.gz
+   :url: https://data.qiime2.org/2023.7/tutorials/atacama-soils/10p/barcodes.fastq.gz
    :saveas: emp-paired-end-sequences/barcodes.fastq.gz
 
 .. _`atacama demux`:
@@ -253,4 +253,4 @@ Califf, Cesar Cardona, Audrey Copeland, Will van Treuren, Karen L. Josephson,
 Rob Knight, Jack A. Gilbert, Jay Quade, J. Gregory Caporaso, and Raina M.
 Maier. mSystems May 2017, 2 (3) e00195-16; DOI: 10.1128/mSystems.00195-16.
 
-.. _sample metadata: https://data.qiime2.org/2023.5/tutorials/atacama-soils/sample_metadata
+.. _sample metadata: https://data.qiime2.org/2023.7/tutorials/atacama-soils/sample_metadata

source/tutorials/chimera.rst

@@ -19,11 +19,11 @@ Start by creating a directory to work in.
 Next, download the necessary files:
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/chimera/atacama-table.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/chimera/atacama-table.qza
    :saveas: atacama-table.qza
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/chimera/atacama-rep-seqs.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/chimera/atacama-rep-seqs.qza
    :saveas: atacama-rep-seqs.qza
 
 Run *de novo* chimera checking

source/tutorials/exporting.rst

@@ -17,7 +17,7 @@ Exporting a feature table
 A ``FeatureTable[Frequency]`` artifact will be exported as a `BIOM v2.1.0 formatted file`_.
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/exporting/feature-table.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/exporting/feature-table.qza
    :saveas: feature-table.qza
 
 .. command-block::
@@ -32,7 +32,7 @@ Exporting a phylogenetic tree
 A ``Phylogeny[Unrooted]`` artifact will be exported as a `newick formatted file`_.
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/exporting/unrooted-tree.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/exporting/unrooted-tree.qza
    :saveas: unrooted-tree.qza
 
 .. command-block::

source/tutorials/feature-classifier.rst

@@ -25,15 +25,15 @@ Two elements are required for training the classifier: the reference sequences a
 We will also download the representative sequences from the `Moving Pictures`_ tutorial to test our classifier.
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/training-feature-classifiers/85_otus.fasta
+   :url: https://data.qiime2.org/2023.7/tutorials/training-feature-classifiers/85_otus.fasta
    :saveas: 85_otus.fasta
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/training-feature-classifiers/85_otu_taxonomy.txt
+   :url: https://data.qiime2.org/2023.7/tutorials/training-feature-classifiers/85_otu_taxonomy.txt
    :saveas: 85_otu_taxonomy.txt
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/training-feature-classifiers/rep-seqs.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/training-feature-classifiers/rep-seqs.qza
    :saveas: rep-seqs.qza
 
 Next we import these data into QIIME 2 Artifacts. Since the Greengenes reference taxonomy file (:file:`85_otu_taxonomy.txt`) is a tab-separated (TSV) file without a header, we must specify ``HeaderlessTSVTaxonomyFormat`` as the *source format* since the default *source format* requires a header.

source/tutorials/filtering.rst

@@ -19,23 +19,23 @@ First, create a directory to work in and change to that directory.
 Download the data we'll use in the tutorial. This includes sample metadata, a feature table, and a distance matrix:
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/moving-pictures/sample_metadata.tsv
+   :url: https://data.qiime2.org/2023.7/tutorials/moving-pictures/sample_metadata.tsv
    :saveas: sample-metadata.tsv
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/filtering/table.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/filtering/table.qza
    :saveas: table.qza
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/filtering/distance-matrix.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/filtering/distance-matrix.qza
    :saveas: distance-matrix.qza
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/filtering/taxonomy.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/filtering/taxonomy.qza
    :saveas: taxonomy.qza
 
 .. download::
-   :url: https://data.qiime2.org/2023.5/tutorials/filtering/sequences.qza
+   :url: https://data.qiime2.org/2023.7/tutorials/filtering/sequences.qza
    :saveas: sequences.qza
 
 Filtering feature tables