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SCarborSNV is an efficient algorithm for phylogeny aware genotyping of single cell genomes, using dynamic programming and neighbor joining.

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SCarborSNV

SCarborSNV is an efficient algorithm for phylogeny aware genotyping of single cell genomes. SCarborSNV uses dynamic programming to compute the expected evolutionary distance between pairs of cells, then missing information is inferred from an approximate phylogeny built by neighbor joining.

Installation

Clone SCarborSNV from github: git clone https://github.com/coldham10/SCarborSNV.git

To install, in the newly created directory: make

Running ScarborSNV

SCarborSNV takes as input an mpileup file or stream. You must specify the number of cells in the pieup with the -m option.

From a pre-existing mpileup file with 10 cells: ./SCarborSNV -m 10 -p tencells.mpileup

Or, for example, to use a compressed mpileup file: zcat twentycells.mpileup.gz | ./SCarborSNV -m 20

Command line options are:

Short option Long option Description
-m --n-cells (Required) Number of cells in the mpileup
-p --pileup-file Name of mpileup file to read
-o --vcf-file Name of output file. Defaults to SCarborSNV_out.vcf
--lambda Somatic mutation rate
--mu Germline mutation rate
--p-haploid Prior probability that any given locus has experienced LOH
--p-clonal Prior probability that any SNV is public
--temp-file Name of necessary temp file. By default is written to /tmp. Warning: If running multiple instances of SCarborSNV concurrently you must specify different temp file locations
--amp-err Probability of a base substitution due to amplification error
--p-ado Prior probability that a base has experienced allelic dropout
--candidate-threshold Threshold on posterior probability of alternate allele count being 0 at a locus. Loci with P(aac = 0) < threshold will be considered as candidate mutants.

Licence

The SCarborSNV software is freely available under the GPL v.3.

Copyright 2019 Christopher Oldham

Christopher Oldham

University of Connecticut

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SCarborSNV is an efficient algorithm for phylogeny aware genotyping of single cell genomes, using dynamic programming and neighbor joining.

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