MAINT: add arXiv citation

q2_boots/citations.bib

@@ -0,0 +1,40 @@
+@ARTICLE{Raspet2024,
+  title         = "Facilitating bootstrapped and rarefaction-based microbiome
+                   diversity analysis with {q2}-boots",
+  author        = "Raspet, Isaiah and Gehret, Elizabeth and Herman, Chloe and
+                   Meilander, Jeff and Manley, Andrew and Simard, Anthony and
+                   Bolyen, Evan and Caporaso, J Gregory",
+  journal       = "arXiv [q-bio.QM]",
+  abstract      = "Background: We present q2-boots, a QIIME 2 plugin that
+                   facilitates bootstrapped and rarefaction-based microbiome
+                   diversity analysis. This plugin provides eight new actions
+                   that allow users to apply any of thirty different alpha
+                   diversity metrics and twenty-two beta diversity metrics to
+                   bootstrapped or rarefied feature tables, using a single QIIME
+                   2 Pipeline command, or more granular QIIME 2 Action commands.
+                   Results: Given a feature table, an even sampling depth, and
+                   the number of iterations to perform (n), the command qiime
+                   boots core-metrics will resample the feature table n times
+                   and compute alpha and beta diversity metrics on each
+                   resampled table. The results will be integrated in summary
+                   data artifacts that are identical in structure and type to
+                   results that would be generated by applying diversity metrics
+                   to a single table. This enables all of the same downstream
+                   analytic tools to be applied to these tables, and ensures
+                   that all collected data is considered when computing
+                   microbiome diversity metrics. Conclusions: A challenge of
+                   this work was deciding how to integrate distance matrices
+                   that were computed on n resampled feature tables, as a simple
+                   average of pairwise distances (median or mean) does not
+                   account for the structure of distance matrices. q2-boots
+                   provides three options, and we show here that the results of
+                   these approaches are highly correlated. q2-boots is free and
+                   open source. Source code, installation instructions, and a
+                   tutorial can be found at
+                   https://github.com/caporaso-lab/q2-boots.",
+  month         =  aug,
+  year          =  2024,
+  archivePrefix = "arXiv",
+  primaryClass  = "q-bio.QM",
+  doi           = "https://doi.org/10.48550/arXiv.2408.05420"
+}

q2_boots/plugin_setup.py

@@ -7,7 +7,7 @@
 # ----------------------------------------------------------------------------
 
 from qiime2.plugin import (Plugin, Int, Range, Collection, Str, Choices, Bool,
-                           Float, Metadata, Visualization)
+                           Float, Metadata, Visualization, Citations)
 
 from q2_types.feature_table import (
     FeatureTable, Frequency, RelativeFrequency, PresenceAbsence
@@ -31,6 +31,7 @@
                                 _core_metrics_bootstrap_example,
                                 _core_metrics_rarefaction_example)
 
+citations = Citations.load("citations.bib", package='q2_boots')
 
 plugin = Plugin(
     name='boots',
@@ -41,7 +42,8 @@
                        'analyses.'),
     description=('A plugin providing bootstrapped and rarefaction-based '
                  '(i.e., resampled) diversity analyses, designed to mirror the '
-                 'interface of q2-diversity.')
+                 'interface of q2-diversity.'),
+    citations=[citations['Raspet2024']]
 )
 
 

setup.py

@@ -26,6 +26,6 @@
     entry_points={
         "qiime2.plugins": ["q2-boots=q2_boots.plugin_setup:plugin"]
     },
-    package_data={},
+    package_data={'q2_boots': ['citations.bib']},
     zip_safe=False,
 )