DSRC is a toolkit designed for efficient high-performance compression of sequencing reads stored in FASTQ format, where it's main features are:
- Effective multithreaded compression of FASTQ files.
- Full support for Illumina, ABI SOLiD, and 454/Ion Torrent dataset formats with non-standard (AGCTN) IUPAC base values.
- Support for lossy quality values compression using Illumina binning scheme.
- Support for lossy IDs compression keeping only key fields selected by user.
- Pipes support for easy integration with current pipelines.
- Python and C++ libraries allowing to integrate DSRC archives in own applications.
- Availability for Linux, Mac OSX and Windows 64-bit operating systems.
- Open source C++ code under GNU GPL 2 license.
For more information please check out the official website.
Pre-built binaries and libraries for Linux, Mac OSX and Windows platforms can be downloaded from the official website.
DSRC binaries and C++ library can be compiled in two ways, depending on the selection of multithreading support library - for each a different makefile file is provided. In the first case, boost::threads library will be used, which is needed to be present on the build system. In the second - g++ compiler with c++11 support (version >= 4.8).
By default, binaries and libraries are compiled using g++, however compiling using Clang or Intel icpc should also succeeed without any problems.
On Mac OSX Clang compiler will be used with c++11 support, so make sure to have Clang in version >= 3.3 installed.
To compile DSRC under Windows OS, Microsoft Visual Studio 2010 or 2012 is required. DSRC binaries and C++ library can be compiled in two ways, depending on the selection of multithreading support library - for each a different VS solution file is provided. When compiling using VS2010 the boost::threads library will be used to provide multithreading support, so make sure to have boost::threads library installed and boost library paths properly configured in Visual Studio. In case of using VS2012 c++11 standard implementation will be used to provide threading support.
There should be also no problems when compiling DSRC using MinGW-32-x64 with provided Makefile files.
To build DSRC Python library, boost::python library in development version and boost::build tool bjam are need to be present on the system. Next, in the Jamroot configuration file in py directory a local boost installation directory needs to be specified:
# To compile DSRC Python module please specify your boost installation directory below
#
use-project boost
: /absolute/path/to/boost/directory/ ;
Python library will be built using a default compilation toolset available on the build platform (auto selected by bjam), however in order to specify a different one append
<toolset>name
to the compilation flags as exmplained in the Jamroot file
# Specify toolset according to your platform manually in case of compilation problems in form: '<toolset>gcc'
# Available toolsets:
# - Windows: msvc-*
# - Linux: gcc, clang
# - Mac OSX: darwin, gcc
: <variant>release <address-model>64 <link>shared <runtime-link>shared <debug-symbols>off <inlining>full <optimization>speed <warnings>on <cxxflags>"-O2 -m64 -D_FILE_OFFSET_BITS=64 -D_LARGEFILE_SOURCE -DUSE_BOOST_THREAD" ;
To compile DSRC using boost::threads with static linking, in the main directory type:
make bin
To compile DSRC using g++ >= 4.8 with c++11 standard and dynamic linking:
make -f Makefile.c++11 bin
The resulting dsrc binary will be placed in bin subdirectory.
To compile C++ DSRC library using boost::threads:
make lib
To compile DSRC using g++ >= 4.8 with c++11:
make -f Makefile.c++11 lib
The resulting libdsrc.a library will be placed in lib subdirectory.
To compile DSRC Python library:
make pylib
The resulting pydsrc.so library will be available in py subdirectory.
To compile DSRC binary, in the main directory type:
make -f Makefile.osx bin
The resulting dsrc binary will be placed in bin subdirectory.
To compile DSRC C++ library:
make -f Makefile.osx lib
The resulting libdsrc.a library will be placed in lib subdirectory.
To compile DSRC Python library:
make -f Makefile.osx pylib
The resulting pydsrc.so library will be available in py subdirectory.
To compile DSRC using Visual Studio 2010 with boost::threads for multithreading support use the dsrc20-vs2k10.sln solution file. However, to compile DSRC using Visual Studio 2012 with c++11 threads use the dsrc20-vs2k12.sln.
To compile DSRC executable, select Release|x64 configuration and build.
The resulting dsrc.exe executable will be placed in bin subdirectory.
To compile DSRC library, select Release Lib|x64 configuration and build.
The resulting dsrc.lib library will be placed in lib subdirectory.
To compile DSRC Python library in the py subdirectory type:
bjam
The resulting pydsrc.pyd library will be available in py subdirectory.
DSRC can be run from the command prompt:
dsrc <c|d> [options] <input_file_name> <output_file_name>
in one of two modes:
c— compression,d— decompression.
-d<n>— DNA compression mode:0–3, default:0-q<n>— Quality compression mode:0–2, default:0-f<1,...>— keep only those fields no. in ID field string, default:-b<n>— FASTQ input buffer size in MB, default:8-m<n>— Automated compression mode (one of the three preset combination of other pa- rameters):0–2-o<n>— Quality offset, 0 for auto selection, default:0-l— use Quality lossy mode (Illumina binning scheme), default:false-c— calculate and check CRC32 checksum calculation per block (slows the compression about twice), default:false
-m0— fast mode, equivalent to:-d0 -q0 -b8-m1— medium mode, equivalent to:-d2 -q2 -b64-m2— best mode, equivalent to:-d3 -q2 -b256
-t<n>— processing threads number, default: max available hardware threads-s— use stdin/stdout for reading/writing raw FASTQ files data (stderr is used for info/warning messages)
Compress SRR001471.fastq file saving DSRC archive to SRR001471.dsrc:
dsrc c SRR001471.fastq SRR001471.dsrc
Compress file in the fast mode with CRC32 checking and using 4 threads:
dsrc c -m0 -c -t4 SRR001471.fastq SRR001471.dsrc
Compress file using DNA and Quality compression level 2 and using 512 MB buffer:
dsrc c -d2 -q2 -b512 SRR001471.fastq SRR001471.dsrc
Compress file in the best mode with lossy Quality mode and preserving only 1–4 fields from
record IDs:
dsrc c -m2 -l -f1,2,3,4 SRR001471.fastq SRR001471.dsrc
Compress in the best mode reading raw FASTQ data from stdin:
cat SRR001471.fastq | dsrc c -m2 -s SRR001471.dsrc
Decompress SRR001471.dsrc archive saving output FASTQ file to SRR001471.out.fastq:
dsrc d SRR001471.dsrc SRR001471.out.fastq
Decompress archive using 4 threads and streaming raw FASTQ data to stdout:
dsrc d -t4 -s SRR001471.dsrc > SRR001471.out.fastq