A Scalable GPU System for Pairwise Whole Genome Alignments based on LASTZ's seed-filter-extend paradigm.
The system has been tested on all the AWS G3 and P3 GPU instances with AMI Ubuntu Server 18.04 LTS (HVM), SSD Volume Type (ami-0fc20dd1da406780b (64-bit x86))
git clone https://github.com/gsneha26/SegAlign.git
export PROJECT_DIR=$PWD/SegAlign
The following dependencies are required by SegAlign:
The dependencies can be installed with the given script as follows, which might take a while (only installs the dependencies not present already). This script requires sudo to install most packages at the system level. Using the -c
option skips CUDA installation [the CUDA toolkit binaries should be in $PATH
for SegAlign].
cd $PROJECT_DIR
./scripts/installUbuntu.sh
run_segalign target query [options]
run_segalign --help
cd $PROJECT_DIR
mkdir test
cd test
wget https://hgdownload.soe.ucsc.edu/goldenPath/ce11/bigZips/ce11.2bit
wget https://hgdownload-test.gi.ucsc.edu/goldenPath/cb4/bigZips/cb4.2bit
twoBitToFa ce11.2bit ce11.fa
twoBitToFa cb4.2bit cb4.fa
run_segalign ce11.fa cb4.fa --output=ce11.cb4.maf
run_segalign_repeat_masker sequence [options]
run_segalign_repeat_masker --help
cd $PROJECT_DIR
mkdir test_rm
cd test_rm
wget https://hgdownload.soe.ucsc.edu/goldenPath/ce11/bigZips/ce11.2bit
twoBitToFa ce11.2bit ce11.fa
run_segalign_repeat_masker ce11.fa --output=ce11.seg
wget https://hgdownload.soe.ucsc.edu/goldenPath/ce11/bigZips/ce11.2bit
wget https://hgdownload-test.gi.ucsc.edu/goldenPath/cb4/bigZips/cb4.2bit
sudo docker run -v $(pwd):/data -it gsneha/segalign:v0.1.2 \
twoBitToFa \
/data/ce11.2bit \
/data/ce11.fa
sudo docker run -v $(pwd):/data -it gsneha/segalign:v0.1.2 \
twoBitToFa \
/data/cb4.2bit \
/data/cb4.fa
sudo docker run --ipc=host --gpus all -v $(pwd):/data -it gsneha/segalign:v0.1.2 \
run_segalign \
/data/ce11.fa \
/data/cb4.fa \
--output=/data/ce11.cb4.maf
wget https://hgdownload.soe.ucsc.edu/goldenPath/ce11/bigZips/ce11.2bit
sudo docker run -v $(pwd):/data -it gsneha/segalign:v0.1.2 \
twoBitToFa \
/data/ce11.2bit \
/data/ce11.fa
sudo docker run --ipc=host --gpus all -v $(pwd):/data -it gsneha/segalign:v0.1.2 \
run_segalign_repeat_masker \
/data/ce11.fa \
--output=/data/ce11.seg
S. Goenka, Y. Turakhia, B. Paten and M. Horowitz, "SegAlign: A Scalable GPU-Based Whole Genome Aligner," in 2020 SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, 2020 pp. 540-552. doi: 10.1109/SC41405.2020.00043