A Scalable GPU System for Pairwise Whole Genome Alignments based on LASTZ's seed-filter-extend paradigm.
- Overview
- Dependencies
- How to run SegAlign
- How to run SegAlign repeat masker
- Running Docker Image
- Citing SegAlign
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))
- Clone SegAlign repository (https://github.com/gsneha26/SegAlign)
git clone https://github.com/gsneha26/SegAlign.git export PROJECT_DIR=$PWD/SegAlign The following dependencies are required by SegAlign:
- NVIDIA CUDA 10.2 toolkit
- CMake 3.8
- Intel TBB library
- libboost-all-dev
- parallel
- zlib
- LASTZ 1.04.15
- faToTwoBit, twoBitToFa (from kentUtils)
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
run_segalign target query [options] - For a list of 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
run_segalign_repeat_masker sequence [options] - For a list of 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