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vireoSNP - donor deconvolution for multiplexed scRNA-seq data

Project description

Vireo: Variational Inference for Reconstructing Ensemble Origin by expressed SNPs in multiplexed scRNA-seq data.

The name vireo follows the theme from cardelino (for clone deconvolution), while the Python package name is vireoSNP to aviod name confilict on PyPI.

Installation

The easiest way is to install via PyPI by typing this line is terminal:

pip install vireoSNP

Alternatively, you can always download this repository and install manually:

python setup.py install

For more options of installation, see the full installation.

Usage and manual

Genotyping for each cell (pre-step)

There might be some bioinformatics efforts in this step, however, a few existing software can provide a solution. There are often two steps for this:

  1. identify candidate SNPs: known common SNPs / freebayes / cellSNP

  2. genotype candidate SNPs in each cell: cellSNP / vartrix / bcftools mpileup

See more introduction in the genotyping section.

Demultiplexing from allelic expression

This python package offers a set of utilities functions and an executable command line vireo for donor deconvolution in any of these four situations:

  1. without any genotype:

    vireo -c $CELL_FILE -N $n_donor -o $OUT_DIR
  2. with genotype for all samples (tag via -t: GT, GP, or PL)

    vireo -c $CELL_FILE -d $DONOR_GT_FILE -o $OUT_DIR
  3. with genotype for part of the samples

    vireo -c $CELL_FILE -d $DONOR_GT_FILE -o $OUT_DIR -N $n_donor
  4. with genotype but not confident

    vireo -c $CELL_FILE -d $DONOR_GT_FILE -o $OUT_DIR --forceLearnGT

For details, see the full manual or type “vireo -h” for all arguments. We also provide a demo.sh for running the test data sets in this repo.

Reference

Yuanhua Huang, Davis J. McCarthy, and Oliver Stegle. Vireo: Bayesian demultiplexing of pooled single-cell RNA-seq data without genotype reference. bioRxiv (2019): 598748.

Project details


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