semvec/pypi-packages huggingface dataset:
scmer-lshh125 0.1.0a0
Manifold preserving marker selection for single-cell data
Requires Python: >=3.6

# SCMER - Manifold Preserving Feature Selection [![Documentation Status](https://readthedocs.org/projects/scmer/badge/?version=latest)](https://scmer.readthedocs.io/en/latest/?badge=latest)

SCMER is a feature selection methods designed for single-cell data analysis. 
It selects a compact sets of markers that preserve the manifold in the original data.
It can also be used for data integration by using features in one modality to match the manifold of another modality.

## Tutorials ##
Tutorials are available at https://scmer.readthedocs.io/en/latest/examples.html

You may start with the [Melanoma data (Tiorsh et al.)](https://scmer.readthedocs.io/en/latest/melanoma.html).

## Full Documentation ##
Detailed documentation is available at https://scmer.readthedocs.io/en/latest/

Preprint: https://www.biorxiv.org/content/10.1101/2020.12.01.407262v1.full

The mechanism and capabilities of SCMER is detailed in our pre-print [Single-Cell Manifold Preserving Feature Selection (SCMER)](https://www.biorxiv.org/content/10.1101/2020.12.01.407262v1)