pairsnp
A set of scripts for very quickly obtaining pairwise SNP distance matrices from multiple sequence alignments using sparse matrix libraries to improve performance.
For larger alignments such as the Maela pneumococcal data set (3e5 x 3e3) the c++ version is approximately an order of magnitude faster than approaches based on pairwise comparison of every site such as snp-dists from which the skeleton code for the c++ version was taken.
In order to be most useful implementations in R, python and c++ are available.
| Implementation | Travis |
|---|---|
| R |  |
| python |  |
| c++ |  |
Installation
R
The R version can be installed using devtools or downloaded from its repository
#install.packages("devtools")
devtools::install_github("gtonkinhill/pairsnp-r")
python
The python version can be installed using pip or by downloading the repository and running setup.py.
python -m pip install pairsnp
or alternatively download the repository and run
cd ./pairsnp-python/
python ./setup.py install
c++
The c++ version can be installed manually, by downloading the binaries in this repository, or with conda as
conda install -c gtonkinhill pairsnp
The c++ code relies on a recent version of Armadillo (currently tested on v8.6) and after downloading the repository can be built by running
cd ./pairsnp-cpp/
./configure
make
make install
The majority of time is spend doing sparse matrix multiplications so linking to a parallelised library for this is likely to improve performance further.
At the moment you may need to run touch ./* before compiling to avoid some issues with time stamps.
Quick Start
R
library(pairsnp)
fasta.file.name <- system.file("extdata", "seqs.fa", package = "pairsnp")
sparse.data <- import_fasta_sparse(fasta.file.name)
d <- snp_dist(sparse.data)
python
The python version can be run from the python interpreter as
from pairsnp import calculate_snp_matrix, calculate_distance_matrix
sparse_matrix, consensus, seq_names = calculate_snp_matrix(fasta.file.name)
d = calculate_distance_matrix(sparse_matrix, consensus, "dist", False)
alternatively if installed using pip it can be used at the command line as
pairsnp -f /path/to/msa.fasta -o /path/to/output.csv
additional options include
Program to calculate pairwise SNP distance and similarity matrices.
optional arguments:
-h, --help show this help message and exit
-t {sim,dist}, --type {sim,dist}
either sim (similarity) or dist (distance) (default).
-n, --inc_n flag to indicate differences to gaps should be
counted.
-f FILENAME, --file FILENAME
location of a multiple sequence alignment. Currently
only DNA alignments are supported.
-z, --zipped Alignment is gzipped.
-c, --csv Output csv-delimited table (default tsv).
-o OUTPUT, --out OUTPUT
location of output file.
c++
The c++ version can be run from the command line as
pairsnp -c msa.fasta > output.csv
additional options include
SYNOPSIS
Pairwise SNP similarity and distance matrices using fast matrix algerbra libraries
USAGE
pairsnp [options] alignment.fasta[.gz] > matrix.csv
OPTIONS
-h Show this help
-v Print version and exit
-s Find the similarity matrix
-c Output CSV instead of TSV
-n Count comparisons with Ns (off by default)
-b Blank top left corner cell instead of 'pairsnp 0.0.1'
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent