update docs

Author: josesho

docs/source/about.rst

@@ -7,7 +7,7 @@ About
 
 Authors
 --------
-DABEST is written in Python by `Joses W. Ho <https://twitter.com/jacuzzijo>`_, with design and input from `Adam Claridge-Chang <https://twitter.com/adamcchang>`_ and other lab members.
+DABEST is written in Python by `Joses W. Ho <https://twitter.com/jacuzzijo>`_, with design and input from `Adam Claridge-Chang <https://twitter.com/adamcchang>`_ and other `lab members <https://www.claridgechang.net/people.html>`__.
 
 To find out more about the authors’ research, please visit the `Claridge-Chang lab webpage <http://www.claridgechang.net/>`_.
 

docs/source/citation.rst

@@ -0,0 +1,17 @@
+.. _Citing DABEST:
+
+
+=============
+Citing DABEST
+=============
+
+If your publication features a graphic generated with this software library, please cite the following publication.
+
+**Moving beyond P values: Everyday data analysis with estimation plots**
+Joses Ho, Tayfun Tumkaya, Sameer Aryal, Hyungwon Choi, Adam Claridge-Chang
+
+`Nature Methods` 2019, 1548-7105. `doi:10.1038/s41592-019-0470-3 <https://doi.org/10.1038/s41592-019-0470-3>`__
+
+`Free-to-view PDF <https://rdcu.be/bHhJ4>`__
+
+`Paywalled publisher site <https://www.nature.com/articles/s41592-019-0470-3>`__

docs/source/getting-started.rst

@@ -8,7 +8,7 @@ Getting Started
 Requirements
 ------------
 
-Python 3.7 is strongly recommended. DABEST has also been tested with Python 3.5 and 3.6.
+Python 3.8 is strongly recommended. DABEST has also been tested with Python 3.5, 3.6, and 3.7.
 
 In addition, the following packages are also required (listed with their minimal versions):
 
@@ -17,7 +17,7 @@ In addition, the following packages are also required (listed with their minimal
 * `matplotlib 3.0 <https://www.matplotlib.org>`_
 * `pandas 0.25.3 <https://pandas.pydata.org>`_
 * `seaborn 0.9 <https://seaborn.pydata.org>`_
-* `lqrt 0.3.2 <https://github.com/alyakin314/lqrt>`_
+* `lqrt 0.3 <https://github.com/alyakin314/lqrt>`_
 
 To obtain these package dependencies easily, it is highly recommended to download the `Anaconda <https://www.continuum.io/downloads>`_ distribution of Python.
 

docs/source/index.rst

@@ -19,10 +19,10 @@ Analyze your data with estimation statistics!
 News
 ----
 January 2020:
- - v0.3.0 released. Approximate permutation tests have been added, and are now the default p-values reported in the textual output. The LqRT tests were also refactored to a user-callable property.
+ - v0.3.0 released. Approximate permutation tests have been added, and are now the default p-values reported in the textual output. The LqRT tests were also refactored to a user-callable property. For more information, see the :doc:`release-notes`.
 
 December 2019:
-  - v0.2.8 released. This release adds the `Lq-Likelihood-Ratio-Type Test <https://github.com/alyakin314/lqrt>`_ in the statistical output, and also a bugfix for  slopegraph and reference line keyword parsing. For more information, see the :doc:`release-notes`.
+  - v0.2.8 released. This release adds the `Lq-Likelihood-Ratio-Type Test <https://github.com/alyakin314/lqrt>`_ in the statistical output, and also a bugfix for  slopegraph and reference line keyword parsing. 
 
 October 2019:
   - v0.2.7 released. A minor bugfix in the handling of wide datasets with unequal Ns in each group. 
@@ -47,7 +47,7 @@ Contents
 --------
 
 .. toctree::
-  :maxdepth: 2
+  :maxdepth: 1
 
   robust-beautiful
   bootstraps
@@ -56,3 +56,4 @@ Contents
   release-notes
   api
   about
+  citation

docs/source/tutorial.rst

@@ -1382,7 +1382,7 @@ Applying style sheets
 
 *Implemented in v0.2.0*.
 
-``dabest`` can now apply `matplotlib style
+``dabest`` can apply `matplotlib style
 sheets <https://matplotlib.org/tutorials/introductory/customizing.html>`__
 to estimation plots. You can refer to this
 `gallery <https://matplotlib.org/3.0.3/gallery/style_sheets/style_sheets_reference.html>`__