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Denoising scRNA-seq in a smart and efficient way.

Project description

cellsweep

Sweep out noisy counts from single-cell RNA-seq data with CellSweep!

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Install

Basic use

pip install cellsweep

To run notebooks:

pip install cellsweep[analysis]

To remake figures from the paper:

git clone https://github.com/pachterlab/cellsweep.git
cd cellsweep
conda env create -f environment.yml
pip install cellsweep[analysis]==0.1.0

Quickstart

CellSweep has a single function denoise_count_matrix that takes a raw count matrix in an AnnData object and produces a denoised count matrix in another AnnData object. See a simple, fully worked example in the notebooks/intro.ipynb Jupyter Notebook.

Python API

import cellsweep
adata_cellsweep = cellsweep.denoise_count_matrix(adata_raw_path, adata_out=adata_cellsweep_path)  # assumes that adata_raw_path is an h5ad file or AnnData object with a column adata.obs['celltype'] indicating celltype

# for help
help(cellsweep.denoise_count_matrix)

Command line interface

cellsweep denoise_count_matrix -o adata_cellsweep.h5ad adata_raw.h5ad  # assumes that adata_raw.h5ad is an h5ad file with a column adata.obs['celltype'] indicating celltype

# for help
cellsweep denoise_count_matrix --help

There are many utility functions in the cellsweep.utils module for data processing, plotting, and analysis. See examples in our Jupyter Notebooks.

Tutorials

We have several Jupyter Notebooks demonstrating the use of CellSweep for denoising count matrices and analyzing the results. See the notebooks folder in the repository.

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