single-cell-benchmark

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single-cell-benchmark

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# Comprehensive benchmark of dimension reduction methods for single-cell data analysis

## Software requirements

- [Nextflow](https://www.nextflow.io/)
- Docker or Singularity

## The list of benchmarking datasets

- scATAC-seq: https://1drv.ms/x/s!AuDfAP0z9Zsma9Hsr9Ggoz3MtFU?e=0RKKLU
- scRNA-seq:
- scHi-C:

## How to prepare new benchmark datasets

Benchmark data is stored in `anndata` format. The `anndata` object should contain:

1. `adata.X`: cell by feature count matrix. For scATAC-seq, the format of feature names should be: `chr:start-end`.
2. `adata.obs["cell_annotation"]`: cluster/cell-type annotation of each barcode.
3. `data.obs['batch']`: batch annotation of each barcode (optional).

## How to run benchmark

The pipeline uses docker or singularity containers to run the benchmark. Therefore, you need to install either docker or singularity on your machine.
The pipeline needs to download large data files, so make sure you have enough disk space (>20G) and a fast internet connection.

Use `./bench.sh -profile singularity` or `./bench.sh -profile docker` to run benchmarks.
The benchmark results will be stored in `./results` folder.

See `nextflow.config` for additional configuration options.

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