Awesome

A Scalable GPU System for Pairwise Whole Genome Alignments based on LASTZ's seed-filter-extend paradigm.

Overview
Dependencies
How to run SegAlign
- Running a test
How to run SegAlign repeat masker
- Running a test
Running Docker Image
- Running segalign
- Running segalign_repeat_masker
Citing SegAlign

<a name="overview"></a> Overview

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

<a name="dependencies"></a> Dependencies

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

<a name="run"></a> How to run SegAlign

Run SegAlign

run_segalign target query [options]

For a list of options

run_segalign --help

<a name="test"></a> Running a test

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

<a name="run_rm"></a> How to run SegAlign repeat masker

Run SegAlign repeat masker

run_segalign_repeat_masker sequence [options]

For a list of options

run_segalign_repeat_masker --help

<a name="test_rm"></a> Running a test

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

<a name="docker"></a> Running Docker Image

<a name="d_segalign"></a> Running segalign

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

<a name="d_segalign_rm"></a> Running segalign_repeat_masker

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

<a name="cite_segalign"></a> Citing SegAlign

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