Metadata-Version: 2.4
Name: dropbucket
Version: 0.1.6
Summary: Robust SNP-based demultiplexing tool
Author-email: dongjuleem <ehdwn5170@g.skku.edu>
Maintainer-email: dongjuleem <ehdwn5170@g.skku.edu>
License: MIT
Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy==1.26.4
Requires-Dist: pandas==2.2.3
Requires-Dist: scipy==1.13.1
Requires-Dist: scikit-learn==1.6.1
Dynamic: license-file

[![PyPI version](https://img.shields.io/pypi/v/dropbucket.svg)](https://pypi.org/project/dropbucket/)


## dropbucket
Robust SNP-based demultiplexing tool designed to accurately assign cells to donors in pooled scRNA-seq, even under extremely unbalanced pooling condition and samples with genetically similar genotypes.


## Prerequisites
dropbucket requires the following external tools
- FreeBayes
- Vartrix


## Installation
dropbucket is available through pypi
```
pip install dropbucket
```


## Usage
```
usage: dropbucket [-h] -r REFERENCE -b BAM -c CELLBARCODE -k CLUSTERS -o OUTPUT_DIR

set parameters for demultiplexing

optional arguments:
  -h, --help            show this help message and exit
  -r REFERENCE, --reference REFERENCE
                        reference fasta file
  -b BAM, --bam BAM     possorted_genome_bam file
  -c CELLBARCODE, --cellbarcode CELLBARCODE
                        cell barcode tsv file
  -k CLUSTERS, --clusters CLUSTERS
                        number of clusters
  -o OUTPUT_DIR, --output_dir OUTPUT_DIR
                        directory of output file
```
