cellsweep

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

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]==0.1.1

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)  # see below for expected structure

# for help
help(cellsweep.denoise_count_matrix)

Command line interface

cellsweep denoise_count_matrix -o adata_cellsweep.h5ad adata_raw.h5ad  # see below for expected structure

# 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.

Anndata object

The input Anndata object/h5ad file should have the following structure:

• adata.X : cell count matrix (cells x genes)
• adata.obs:
  • adata.obs['celltype']: a column indicating the cell type of each cell.
  • adata.obs['is_empty'] (optional): a boolean column indicating whether each cell is an empty droplet. If not provided, CellSweep will infer empty droplets using the empty_droplet_method argument.
  • adata.obs['init_alpha'] (optional): a column indicating the initial estimate of the fraction of ambient contamination for each cell. If not provided, CellSweep will use the init_alpha argument.
• adata.var:
  • adata.var['ambient_profile'] (optional): a column indicating the per-gene ambient RNA fraction. If not provided, CellSweep will infer the ambient profile from the data.
• adata.uns:
  • adata.uns['celltype_profile'] (optional): a matrix giving the mean expression for each cell type (K x G). If not provided, CellSweep will infer the cell type profile from the data.
  • adata.uns['celltype_profile_genes'] (optional): a list of gene names corresponding to the columns of celltype_profile.

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.