https://github.com/koonimaru/easy_heatmapper
A python module to create clustered heatmaps and output clusters.
https://github.com/koonimaru/easy_heatmapper
Last synced: 8 months ago
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A python module to create clustered heatmaps and output clusters.
- Host: GitHub
- URL: https://github.com/koonimaru/easy_heatmapper
- Owner: koonimaru
- License: mit
- Created: 2019-09-26T03:15:20.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2020-02-06T00:30:08.000Z (over 6 years ago)
- Last Synced: 2024-12-31T20:20:15.742Z (over 1 year ago)
- Language: Python
- Size: 764 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# easy_heatmapper
A python module to create clustered heatmaps and output clusters.
Introduction
------------
easy_heatmapper is a python module to easily draw clustered heatmaps, clustered scatter plot and write cluster information in a text file.
To draw a heatmap, a function called "heatmapper" uses hierarchical clustering with euclidean distance and ward method. It can also apply PCA, t-SNE, UMAP to reduce the dimension of data before hierarchical clustering.
This module also includes a scatter plot function to plot dimension-reduced data colored by automatically detected clusters with hierarchical clustering.
Installation
------------
System-wide installation..
git clone https://github.com/koonimaru/easy_heatmapper.git
cd easy_heatmapper
sudo pip3 install .
Using a virtual environment..
sudo apt-get install python3-venv #If you do not have one.
git clone https://github.com/koonimaru/easy_heatmapper.git
cd easy_heatmapper
python3 -m venv ./
source bin/activate
pip3 install .
Test installation
-----------------
cd easy_heatmapper
python3 test.py
will create a random heatmapper.
Usage
-----
**easy_heatmapper.heatmapper(X, xLabels=[],yLabels=[], save=, WRITE_CLUSTER=True, methods="tsne",CPU=, cluster_both=True, SHOW=True, tCOLOR='nipy_spectral', hCOLOR="YlGnBu", _spectral=18, _n_neighbors=5, _min_dist=0.1, _perplexity=50, _n_iter=5000, _pca_comp=2, _color_threshold=0.1)**
X: M x N array.
xLabels: N array. The labels/names of data X by column.
yLabels: M array. The labels/names of data X by row.
save: a saving directory with a prefix, e.g., "/home/foo/test". Default is a current directory. If you set as "", no files will be saved.
WRITE_CLUSTER: True or False. Choose if cluster information is output or not. Default=True.
methods: "", "tsne", "umap", "pca". Dimension reduction methods to apply before hierarchical clustering.
CPU: CPU number to use. It has effect only when tsne methods is used.
cluster_both: True or False. If True, cluster both x and y axis of data.
SHOW: True or False. If True, show a heatmap in runtime.
tCOLOR: Takes the name of matlab colormaps. It sets the colors of clusters in a dendrogram. Default: 'nipy_spectral'.
hCOLOR: Takes the name of matlab colormaps. It sets the colors of clusters in a heatmap. Default: "YlGnBu".
_spectral: Takes an integer. The number of colors to use. If you see different clusters with a same color, increase this number. Default: 18.
_color_threshold: Takes a float number from 0.0 to 1.0.
**easy_heatmapper.scatter(X,yLabels=[], save=, WRITE_CLUSTER=True, methods="tsne",CPU=os.cpu_count()//2, SHOW=True, COLOR='nipy_spectral', _spectral=18,_n_neighbors=5, _min_dist=0.1, _perplexity=50, _n_iter=5000, _color_threshold=0.1)**
X: M x N array.
xLabels: N array. The labels/names of data X by column.
yLabels: M array. The labels/names of data X by row.
save: a saving directory with a prefix, e.g., "/home/foo/test". Default is a current directory. If you set as "", no files will be saved.
WRITE_CLUSTER: True or False. Choose if cluster information is output or not. Default=True.
methods: Takes "", "tsne", "umap", "pca". Dimension reduction methods to apply before hierarchical clustering.
CPU: CPU number to use. It has effect only when tsne methods is used. Default is half of available CPUs.
cluster_both: True or False. If True, cluster both x and y axis of data. Default=True.
SHOW: True or False. If True, show a heatmap in runtime. Default=True.
COLOR: Takes the name of matlab colormaps. It sets the colors of clusters. Default: 'nipy_spectral'.
_spectral: Takes an integer. the number of colors to use. If you see different clusters with a same color, increase this number.
Example
-------
~~~python
import easy_heatmapper as eh
import numpy as np
#creating noisy matrix
b=np.random.normal(0,1, size=(25,25))
for i in range(10):
b=np.concatenate((b, np.random.normal(i+1, 1, size=(25,25) )), axis=0)
b[:]+=np.arange(25)/5.0
np.random.shuffle(b)
eh.heatmapper(b)
~~~
~~~python
import easy_heatmapper as eh
import numpy as np
#creating noisy matrix
b=np.random.normal(0,1, size=(25,25))
for i in range(10):
b=np.concatenate((b, np.random.normal(i+1, 1, size=(25,25) )), axis=0)
b[:]+=np.arange(25)/5.0
np.random.shuffle(b)
eh.scatter(b)
~~~
~~~python
from sklearn.datasets import load_iris
import easy_heatmapper as eh
iris = load_iris()
X = iris.data
y = iris.target
eh.scatter(X, methods="umap",yLabels=y)
~~~
