Current Version: 1.0.1 Release date: June 8, 2021
Changes in latest version
- Update dependencies
For details of past changes please see CHANGELOG.
SEW is an R program for reference panel free, long read phasing. SEW runs on a single sample given sequencing reads in BAM format, as well as a list of positions to phase, and outputs imputed genotypes in VCF format.
bioconda instructions are below. Otherwise, SEW can be installed in a few ways. The simplest way to get a release is as follows. First, install R. Then, do the following
git clone --recursive https://github.com/Genomicsplc/SEW.git
cd SEW
./scripts/install-dependencies.sh
mkdir -p releases && cd releases
wget https://github.com/Genomicsplc/sew/releases/download/1.0.1/SEW_1.0.1.tar.gz ## or curl -O
R CMD INSTALL SEW_1.0.1.tar.gz
A quick test (using simulated data) can be performed using
wget https://www.well.ox.ac.uk/~rwdavies/ancillary/SEW_example_2019_01_11.tgz ## or curl -O
tar -xzvf SEW_example_2019_01_11.tgz
./SEW.R --chr=10 --bamlist=bamlist.txt --posfile=posfile.txt --phasefile=phasefile.txt --outputdir=./
To install the latest development code in the repository, use ./scripts/build-and-install.sh. To install alternative releases, download the releases from Github, and install using R CMD INSTALL or similar.
If you encounter problems during installation, please consult the STITCH website, or raise an issue.
SEW (as r-sew) can be installed using conda. Full tutorials can be found elsewhere, but briefly, something like this should work
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
conda install r-sew -c defaults -c bioconda -c conda-forge
source activate
R -e 'library("SEW")'
Note that currently the command like SEW.R is not included with the bioconda installation, so from the command line, you can either run something like R -e 'library("SEW"); SEW(chr="10", bamlist="bamlist.txt", posfile="posfile.txt", phasefile="phasefile.txt", outputdir="./")', or clone the repo to get SEW.R.
For a full list of options, in R, query ?SEW, or from the command line, SEW --help. For a brief writeup of commonly used variables, see Options.md. To pass vectors using the command line, do something like SEW.R --unwindwIterations='c(30,60)'.
Copyright 2019, Genomics plc
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
-
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
-
Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
SEW features an expectation-maximization (EM) algorithm that iteratively tries to 1) determine the best parameters of the model given probabilistic read partitions and 2) probabilistically partition reads into two haplotypes given parameters of the model. The EM algorithm is excellent at finding local minima, but relies on initial parameter estimates, and will have difficulty getting to global maxima.
To help overcome this, SEW uses a heuristic. More detail is available in the paper, but briefly, these local, but not global, maxima often reflect where there is good local reconstruction of the two haplotypse, but there is a switchover at some point between the estiamted computational haplotypes and the true haplotypes. The heuristic will, on specified iterations (unwindIterations), check between every pair of SNPs, whether flipping the computational haplotypes at the second SNP and beyond and running the EM algorithm for a few iterations will improve the local fit of the model versus the current configuration.
The current heuristics were developed for use with high coverage long read data. Different depths or length of reads might work best with alternative heuristic settings. For advice, please feel free to open an issue or send an email.
Tests in SEW are split into unit or acceptance run using ./scripts/test-unit.sh and ./scripts/test-acceptance.sh. To run all tests use ./scripts/all-tests.sh, which also builds and installs a release version of SEW. To make compilation go faster do something like export MAKE="make -j 8".
Bowden, R., Davies R. W., Heger A., Pagnamenta A. T., de Cesare M., Oikkonen L. E. et al. Sequencing of human genomes with nanopore technology. Nat. Commun 10, 1869 (2019).
The best way to report bugs or to get help is to open an issue on Github. Alternatively, for more detail questions or other concerns please contact Robert Davies [email protected]