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PyComplexHeatmap Downloads Downloads Downloads

PyComplexHeatmap is a Python package to plot complex heatmap (clustermap). Please click here for documentation.

Documentation:

https://dingwb.github.io/PyComplexHeatmap

PYPI

Wiki

wiki/layout
wiki/Parameters
wiki/Features

Dependencies:

  • matplotlib>=3.4.3
  • numpy
  • pandas
  • scipy
  • fastcluster
pip install --ignore-install matplotlib==3.5.1 numpy==1.20.3 pandas==1.4.1
pip install seaborn #only needed when call functions in tools.py

Citation

Ding, W., Goldberg, D. and Zhou, W. (2023), PyComplexHeatmap: A Python package to visualize multimodal genomics data. iMeta e115. https://doi.org/10.1002/imt2.115

Installation

  1. Install using pip:
pip install PyComplexHeatmap

#upgrade from older version
pip install --upgrade PyComplexHeatmap
  1. Install the developmental version directly from github:
pip install git+https://github.com/DingWB/PyComplexHeatmap

if you have installed it previously and want to update it, please run pip uninstall PyComplexHeatmap and install from github again OR

git clone https://github.com/DingWB/PyComplexHeatmap
cd PyComplexHeatmap
python setup.py install

Usage

1. Simple Guide To Get started.

from PyComplexHeatmap import *

#Generate example dataset (random)
df = pd.DataFrame(['GroupA'] * 5 + ['GroupB'] * 5, columns=['AB'])
df['CD'] = ['C'] * 3 + ['D'] * 3 + ['G'] * 4
df['EF'] = ['E'] * 6 + ['F'] * 2 + ['H'] * 2
df['F'] = np.random.normal(0, 1, 10)
df.index = ['sample' + str(i) for i in range(1, df.shape[0] + 1)]
df_box = pd.DataFrame(np.random.randn(10, 4), columns=['Gene' + str(i) for i in range(1, 5)])
df_box.index = ['sample' + str(i) for i in range(1, df_box.shape[0] + 1)]
df_bar = pd.DataFrame(np.random.uniform(0, 10, (10, 2)), columns=['TMB1', 'TMB2'])
df_bar.index = ['sample' + str(i) for i in range(1, df_box.shape[0] + 1)]
df_scatter = pd.DataFrame(np.random.uniform(0, 10, 10), columns=['Scatter'])
df_scatter.index = ['sample' + str(i) for i in range(1, df_box.shape[0] + 1)]
df_heatmap = pd.DataFrame(np.random.randn(30, 10), columns=['sample' + str(i) for i in range(1, 11)])
df_heatmap.index = ["Fea" + str(i) for i in range(1, df_heatmap.shape[0] + 1)]
df_heatmap.iloc[1, 2] = np.nan

#Annotate the rows with sample4 > 0.5
df_rows = df_heatmap.apply(lambda x:x.name if x.sample4 > 0.5 else None,axis=1)
df_rows=df_rows.to_frame(name='Selected')
df_rows['XY']=df_rows.index.to_series().apply(lambda x:'A' if int(x.replace('Fea',''))>=15 else 'B')

#Create row annotations
row_ha = HeatmapAnnotation(
                           Scatter=anno_scatterplot(df_heatmap.sample4.apply(lambda x:round(x,2)),
                                            height=12,cmap='jet',legend=False),
                           Bar=anno_barplot(df_heatmap.sample4.apply(lambda x:round(x,2)),
                                            height=16,cmap='rainbow',legend=False),
                           selected=anno_label(df_rows,colors='red',relpos=(-0.05,0.4)),
                           label_kws={'rotation':30,'horizontalalignment':'left','verticalalignment':'bottom'},
                            axis=0,verbose=0)

#Create column annotations
col_ha = HeatmapAnnotation(label=anno_label(df.AB, merge=True,rotation=10),
                           AB=anno_simple(df.AB,add_text=True),axis=1,
                           CD=anno_simple(df.CD,add_text=True),
                           EF=anno_simple(df.EF,add_text=True,
                                            legend_kws={'frameon':True}),
                           G=anno_boxplot(df_box, cmap='jet',legend=False),
                           verbose=0)

plt.figure(figsize=(5.5, 6.5))
cm = ClusterMapPlotter(data=df_heatmap, top_annotation=col_ha,right_annotation=row_ha,
                       col_cluster=True,row_cluster=True,
                       col_split=df.AB,row_split=2, 
                       col_split_gap=0.5,row_split_gap=0.8,
                       label='values',row_dendrogram=True,
                       show_rownames=False,show_colnames=True,
                       tree_kws={'row_cmap': 'Set1'},verbose=0,legend_gap=5,
                       cmap='RdYlBu_r',xticklabels_kws={'labelrotation':-45,'labelcolor':'blue'})
#plt.savefig("example0.pdf", bbox_inches='tight')
plt.show()

Example output

Click picture to view the source code

More Examples

https://dingwb.github.io/PyComplexHeatmap/build/html/more_examples.html

Call for Contributions

The PyComplexHeatmap project welcomes your expertise and enthusiasm!

Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact us ([email protected]).

Writing code isn’t the only way to contribute to PyComplexHeatmap. You can also:

  • review pull requests
  • help us stay on top of new and old issues
  • develop tutorials, presentations, and other educational materials
  • maintain and improve our website
  • develop graphic design for our brand assets and promotional materials
  • translate website content
  • help with outreach and onboard new contributors
  • put forward some new ideas about update.