/scDMFK

Single-cell transcriptome data clustering via multinomial modeling and adaptive fuzzy k-means algorithm

Primary LanguagePython

Single-cell transcriptome data clustering via multinomial modeling and adaptive fuzzy k-means algorithm

Architecture

model

Requirement

Python 3.6

Tensorflow 1.14

Keras 2.2

Data availability

The real data sets we used can be download in data.

Quick start

We use the dataset “Park” and scDMFK model to give an example. Please download all code files first. You just run the following code in your command lines:

python run.py --dataname "Park" --model "multinomial" --mode "indirect"

Then you will get the cluster result of “Park” dataset using scDMFK method in ten random seed. The median values of ARI and NMI are 0.832 and 0.776, respectively. Besides, you can also save the clustering label and low-dimensional latent representation for each cell to facilitate your other downstream analysis.

Reference

Our paper is published in Frontiers in Genetics. The details can be seen in article. Please consider citing it.

Contributing

Author email: clandzyy@pku.edu.cn