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sdomanskyi committed Mar 3, 2021
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3 changes: 3 additions & 0 deletions ChangeLog.md
@@ -1,3 +1,6 @@
- 1.3.7.2
* Added documentation of the function makeViolinPlot

- 1.3.7.1
* Added makeViolinPlot visualization function enabling exploratory analysis of the numeric values distributions for comparison between categorical variables

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146 changes: 73 additions & 73 deletions DigitalCellSorter/VisualizationFunctions.py

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1 change: 1 addition & 0 deletions docs/source/VisualizationFunctions.rst
Expand Up @@ -26,6 +26,7 @@ at the stage of post-processing.
visFunctions/makeMarkerExpressionPlot
visFunctions/makeTtestPlot
visFunctions/makePlotOfNewMarkers
visFunctions/makeViolinPlot



43 changes: 43 additions & 0 deletions docs/source/visFunctions/makeViolinPlot.rst
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**Customized violin plot**
==========================

This visualization function can be launched from `class DigitalCellSorter`.
By default the function also exports a summary of the data.

From submodule `VisualizationFunctions`:


.. autoclass:: DigitalCellSorter.VisualizationFunctions.VisualizationFunctions
:noindex:

.. automethod:: makeViolinPlot


**Example with synthetic data:**

.. code-block:: python
data = pd.DataFrame({'Celltype': np.where((np.random.rand(1000)>0.7), 'Epithelial', 'Endothelial'),
'Condition': np.random.rand(1000)>0.3,
'Gene 1': np.log(np.random.rand(1000)*3 + 1),
'Gene 2': np.log(np.random.rand(1000)*1.5 + 1)})
DCS = DigitalCellSorter.DigitalCellSorter()
DCS.makeViolinPlot(data, ['Gene 1', 'Gene 2'],
dimPanels='Celltype', dimCategories='Condition',
title='{name}: {gene}', ylabel='Condition',
pointsSize=5, fontsize=12)
**Example output:**

.. thumbnail:: https://github.com/sdomanskyi/DigitalCellSorter/blob/master/docs/examples/output/violin_plot.png?raw=true
:title: Example
:alt: Cannot load this figure
:align: center
:width: 250px
:height: 250px
:download: false



2 changes: 1 addition & 1 deletion setup.py
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setup(
name='DigitalCellSorter',
packages=find_packages(),
version='1.3.7.1',
version='1.3.7.2',
description='Toolkit for analysis and identification of cell types from heterogeneous single cell RNA-seq data',
long_description_content_type="text/markdown",
long_description=long_description,
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