Metadata-Version: 1.0
Name: cellSNP
Version: 0.0.7
Summary: cellSNP - Analysis of expressed alleles in single cells
Home-page: https://github.com/huangyh09/cellSNP
Author: Yuanhua Huang
Author-email: yuanhua@ebi.ac.uk
License: Apache-2.0
Description-Content-Type: UNKNOWN
Description: =======
        cellSNP
        =======
        
        cellSNP aims to pileup the expressed alleles in single-cell or bulk RNA-seq 
        data, which can be directly used for donor deconvolution in multiplexed single-
        cell RNA-seq data, particularly with cardelino_, an R package, which assigns 
        cells to donors and detects doublets, even without genotyping the given donors.
        
        cellSNP heavily depends on pysam_, a Python interface for samtools and bcftools. 
        This program should give very similar results as samtools/bcftools mpileup, if 
        it isn't the same. Also, there are two major differences comparing to bcftools 
        mpileup:
        
        1. cellSNP can pileup either the whole genome or a list of positions, with 
           directly splitting into a list of cell barcodes, e.g., for 10x genome. With 
           bcftools, you may need to manipulate the RG tag in the bam file first.
        2. cellSNP uses simple filtering for outputting SNPs, i.e., total UMIs or counts
           and minor alleles fractions. The idea here is to keep most information of 
           SNPs and the downstream statistical model can handle adaptively.
        
        
        Installation
        ------------
        
        cellSNP is available through `pypi`_. To install, type the following command 
        line, and add ``-U`` for upgrading:
        
        .. code-block:: bash
        
          pip install cellSNP
        
        Alternatively, you can download or clone this repository and type 
        ``python setup.py install`` to install. In either case, add ``--user`` if you 
        don't have the permission as a root or for your Python environment.
        
        
        Quick usage
        -----------
        
        Once installed, check all arguments by type ``cellSNP -h``. There are three 
        modes of cellSNP:
        
        **Mode 1**: pileup a list of common SNPs for single cells in a big BAM/SAM 
        file. Require: a single BAM/SAM file, e.g., from cellranger, a VCF file for 
        a list of common SNPs. This mode is recommended comparing to mode 2, if a 
        list of common SNP is known, e.g., human.
        
        .. code-block:: bash
        
          cellSNP -s $BAM -b $BARCODE -o $OUT_FILE -R $REGION_VCF -p 20
          
        Recommend filtering SNPs with <20UMIs or <10% minor alleles for downstream 
        donor deconvolution, by adding ``--minMAF 0.1 --minCOUNT 20``
        
        
        **Mode 2**: pileup the whole genome for single cells in a big BAM/SAM file. 
        This mode may give uninformative SNPs, but can be useful when the data set 
        is highly sparse.
        
        .. code-block:: bash
        
          cellSNP -s $BAM -b $BARCODE -o $OUT_FILE -p 22
          
        Recommend filtering SNPs with <100UMIs or <10% minor alleles for saving space
        and speed up inference when pileup whole genome: ``--minMAF 0.1 --minCOUNT 100``
        
        
        **Mode 3**: pileup a list of common SNPs for one or multiple bulk BAM/SAM files.
        Require: one or multiple BAM/SAM files, their according sample ids, and a VCF 
        file for a list of common SNPs.
        
        .. code-block:: bash
        
          cellSNP -s $BAM1,$BAM2,$BAM3 -I sample_id1,sample_id2,sample_id3 -o $OUT_FILE -R $REGION_VCF -p 20
          
        Set filtering thresholds according to the downstream analysis.
        
        
        
        .. note::
        
           - For lift over SNP positions in vcf file from one genome build to another, 
             see our `LiftOver_vcf`_ wrap function.
           - For release notes, see `release.rst`_.
        
        .. _cardelino: https://github.com/PMBio/cardelino
        .. _pysam: https://github.com/pysam-developers/pysam
        .. _pypi: https://pypi.org/project/cellSNP/
        .. _LiftOver_vcf: https://github.com/huangyh09/cellSNP/tree/master/liftOver
        .. _release.rst: https://github.com/huangyh09/cellSNP/blob/master/doc/release.rst
        
        
Keywords: allelic expression,single-cell RNA-seq
Platform: UNKNOWN
