PyComplexHeatmap
PyComplexHeatmap is a Python package to plot complex heatmap (clustermap). Please click here for documentation.
Documentation:
https://dingwb.github.io/PyComplexHeatmap
PYPI:
https://pypi.org/project/PyComplexHeatmap/
Wiki
Dependencies:
- matplotlib>=3.4.3
- numpy
- pandas
- scipy
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
Installation
- Install using pip:
pip install PyComplexHeatmap
#upgrade from older version
pip install --upgrade PyComplexHeatmap
- 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 average > 0.3
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')
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)
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
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 (ding.wu.bin.gm@gmail.com).
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.