Merge pull request #20 from sbslee/1.10.0-dev

1.10.0 dev

Author: sbslee

CHANGELOG.rst

@@ -1,8 +1,19 @@
 Changelog
 *********
 
+1.10.0 (2021-07-06)
+-------------------
+
+* :issue:`14`, :issue:`17`: Add the ``group_order`` option to the :meth:`taxa_abundance_bar_plot` method.
+* Fix a minor bug in the :meth:`addbiplot` method when feature is 'Unassigned'.
+* Deprecate the :command:`count-reads` command.
+* :issue:`19`: Remove the ``artist_kwargs`` argument from the following methods:
+
+  - :meth:`ancom_volcano_plot`
+  - :meth:`read_quality_plot`
+
 1.9.0 (2021-06-07)
-----------------------
+------------------
 
 * Add publicly available datasets from QIIME 2 for tutorials.
 * :issue:`14`: Add the ``group`` option to the :meth:`taxa_abundance_bar_plot` method. Using this option will create a bar for each group instead of each sample.

docs/dokdo_cli.rst

@@ -160,23 +160,3 @@ prepare-lefse
                             SQLite 'WHERE' clause specifying sample metadata
                             criteria.
       -h, --help            Show this help message and exit.
-
-count-reads
------------
-
-.. code-block:: console
-
-    $ dokdo count-reads -h
-    usage: dokdo count-reads -i PATH [-d TEXT] [-h]
-
-    Count the number of sequence reads from FASTQ. This command outputs two
-    columns corresponding to the file name and read count, respectively.
-
-    Arguments:
-      -i PATH, --fastq-path PATH
-                            Path to the input FASTQ file or to the input directory
-                            containing FASTQ files. [required]
-      -d TEXT, --delimiter TEXT
-                            Delimiter used to separate the file name and read
-                            count. [default: '\t']
-      -h, --help            Show this help message and exit.

docs/images/ancom_volcano_plot.png

@@ -489,7 +489,7 @@ Differential Abundance
 
 In QIIME 2, differential abundance of bacteria can be tested using the analysis of composition of microbiomes (ANCOM). After each ANCOM, we can make a volcano plot as shown below:
 
-.. image:: images/ancom_volcano_plot.png
+.. image:: images/ancom_volcano_plot_1.png
 
 where the x-axis is centered log-ratio (CLR) of relative abundance and the y-axis is the W value which represents the number of rejected null hypotheses. The W value will be explained in more detail below. If you are not familiar with the CLR transformation, it is defined as:
 

docs/images/ancom_volcano_plot_1.png

@@ -289,43 +289,6 @@ def main():
         help=help_msg
     )
 
-    count_reads_parser = subparsers.add_parser(
-        "count-reads",
-        add_help=False,
-        help="Count the number of sequence reads from FASTQ.",
-        description=("Count the number of sequence reads from FASTQ. "
-                     "This command outputs two columns corresponding "
-                     "to the file name and read count, respectively.")
-    )
-
-    count_reads_parser._optionals.title = "Arguments"
-
-    count_reads_parser.add_argument(
-        "-i",
-        "--fastq-path",
-        metavar="PATH",
-        required=True,
-        help=("Path to the input FASTQ file or to the input "
-              "directory containing FASTQ files. [required]")
-    )
-
-    count_reads_parser.add_argument(
-        "-d",
-        "--delimiter",
-        metavar="TEXT",
-        default="\t",
-        help=("Delimiter used to separate the file name and read "
-              "count. [default: '\\t']")
-    )
-
-    count_reads_parser.add_argument(
-        "-h",
-        "--help",
-        action="help",
-        default=argparse.SUPPRESS,
-        help=help_msg
-    )
-
     args = parser.parse_args()
     command = args.command
     delattr(args, "command")

docs/images/ancom_volcano_plot_2.png

@@ -4,7 +4,6 @@
 from .num2sig import num2sig
 from .wilcoxon import wilcoxon
 from .mannwhitneyu import mannwhitneyu
-from .count_reads_one_file import count_reads_one_file
 
 from .read_quality_plot import read_quality_plot
 from .denoising_stats_plot import denoising_stats_plot
@@ -33,4 +32,4 @@
            'beta_scree_plot', 'beta_parallel_plot', 'distance_matrix_plot',
            'taxa_abundance_bar_plot', 'taxa_abundance_box_plot',
            'ancom_volcano_plot', 'addsig', 'regplot', 'addbiplot',
-           'barplot', 'ordinate', 'pname', 'get_mf', 'count_reads_one_file']
+           'barplot', 'ordinate', 'pname', 'get_mf']

docs/images/read_quality_plot.png

@@ -6,24 +6,21 @@
 from qiime2 import Artifact
 
 def addbiplot(
-    pcoa_results, taxonomy=None, dim=2, scale=1.0,
-    count=5, fontsize=None, name_type='feature',
-    level=None, ax=None, figsize=None
+    pcoa_results, dim=2, scale=1.0, count=5, fontsize=None,
+    name_type='feature', taxonomy=None, level=None, ax=None, figsize=None
 ):
-    """Adds arrows (i.e. features) to a PCoA scatter plot.
+    """
+    Draw arrows (features) to an existing PCoA plot.
 
-    This method can handle both 2D and 3D plots.
+    This method supports both 2D and 3D plots.
 
     Parameters
     ----------
     pcoa_results : str or qiime2.Artifact
         Artifact file or object corresponding to
         PCoAResults % Properties('biplot').
-    taxonomy : str or qiime2.Artifact
-        Artifact file or object corresponding to FeatureData[Taxonomy].
-        Required if ``name_type='taxon'`` or ```name_type='confidence'``.
     dim : [2, 3], default: 2
-        Dimension of the input scatter plot.
+        Dimension of the plot.
     scale : float, default: 1.0
         Scale for arrow length.
     count : int, default: 5
@@ -33,8 +30,12 @@ def addbiplot(
     name_type : ['feature', 'taxon', 'confidence'], default: 'feature'
         Determines the type of names displayed. Using 'taxon' and 'confidence'
         requires taxonomy.
+    taxonomy : str or qiime2.Artifact
+        Artifact file or object corresponding to FeatureData[Taxonomy].
+        Required if ``name_type`` is 'taxon' or 'confidence'.
     level : int, optional
-        Taxonomic rank to be displayed. Only use with ``name_type='taxon'```.
+        Level of taxonomic rank to be displayed. This argument has an effect
+        only when ``name_type`` is 'taxon'.
     ax : matplotlib.axes.Axes, optional
         Axes object to draw the plot onto, otherwise uses the current Axes.
     figsize : tuple, optional
@@ -47,9 +48,9 @@ def addbiplot(
 
     See Also
     --------
-    ordinate
-    beta_2d_plot
-    beta_3d_plot
+    dokdo.api.ordinate
+    dokdo.api.beta_2d_plot
+    dokdo.api.beta_3d_plot
 
     Examples
     --------
@@ -122,6 +123,8 @@ def addbiplot(
         feats = pd.concat([feats, tax_df], axis=1, join='inner')
 
     def f(s):
+        if s == 'Unassigned':
+            return s
         ranks = list(s.split(';'))
         if level is None:
             return s