speedseq | flexible framework for rapid genome analysis
kandi X-RAY | speedseq Summary
kandi X-RAY | speedseq Summary
speedseq is a C library. speedseq has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.
A flexible framework for rapid genome analysis and interpretation. C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.
A flexible framework for rapid genome analysis and interpretation. C Chiang, R M Layer, G G Faust, M R Lindberg, D B Rose, E P Garrison, G T Marth, A R Quinlan, and I M Hall. SpeedSeq: ultra-fast personal genome analysis and interpretation. Nat Meth (2015). doi:10.1038/nmeth.3505.
Support
Quality
Security
License
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Support
speedseq has a low active ecosystem.
It has 281 star(s) with 100 fork(s). There are 46 watchers for this library.
It had no major release in the last 12 months.
There are 64 open issues and 73 have been closed. On average issues are closed in 35 days. There are 4 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of speedseq is v0.1.2
Quality
speedseq has 0 bugs and 0 code smells.
Security
speedseq has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
speedseq code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
speedseq is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
Reuse
speedseq releases are available to install and integrate.
Installation instructions, examples and code snippets are available.
It has 879 lines of code, 40 functions and 4 files.
It has high code complexity. Code complexity directly impacts maintainability of the code.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of speedseq
Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of speedseq
speedseq Key Features
No Key Features are available at this moment for speedseq.
speedseq Examples and Code Snippets
No Code Snippets are available at this moment for speedseq.
Community Discussions
No Community Discussions are available at this moment for speedseq.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install speedseq
Run the example script.
Install git clone --recursive https://github.com/hall-lab/speedseq cd speedseq make
Run the example script cd example ./run_speedseq This should produce the following files: example.bam example.discordants.bam example.splitters.bam example.vcf.gz example.sv.vcf.gz
As a template for installation on other systems, we have provided the exact commands for a full installation of SpeedSeq and GEMINI on a blank [Amazon Linux](Amazon Linux AMI 2014.09.2 (HVM)) box. These commands encompass all of the installation steps outlined below. System paths to SpeedSeq's component software are specified in the speedseq.config file, which should reside in the same directory as the SpeedSeq executable (for alternate locations use the -K flag). Upon installation, SpeedSeq attempts to automatically generate this file, but manual editing may be necessary. The core components enable standard functionality outlined in Quick start. Compilation requires g++ and the standard C and C++ development libraries. Additionally, cmake is required for building the BamTools API within FreeBayes and LUMPY. Essential SpeedSeq components can be installed with make, which produces a log file (install.log) that details the compilation status. The installation is modular, and its units can be built separately with make align, make var, make somatic, make sv, and make realign. This allows installation of only the desired components, eliminating extraneous dependencies. It further allows rebuilding of previously failed components. If any components already exist on the system or fail to install, their paths can be manually specified by editing speedseq.config. Optional components enable advanced features such as variant annotation and read-depth analysis. CNVnator requires the ROOT package as a prerequiste (https://root.cern.ch/drupal/). Please refer to the CNVnator repository for details on installing CNVnator.
Example SpeedSeq installation commands
g++ and the standard C and C++ development libraries (https://gcc.gnu.org/)
CMake (http://www.cmake.org/)
GNU awk and core utils
Python 2.7 (https://www.python.org/) numpy pysam 0.8.0+ scipy
ROOT (https://root.cern.ch/) (required if running CNVnator)
Variant Effect Predictor (http://www.ensembl.org/info/docs/tools/vep/index.html) (required if annotating VCF files)
BWA (http://bio-bwa.sourceforge.net/)
FreeBayes (https://github.com/ekg/freebayes)
LUMPY (https://github.com/arq5x/lumpy-sv)
Sambamba (http://lomereiter.github.io/sambamba/)
SAMBLASTER (https://github.com/GregoryFaust/samblaster)
Vawk (https://github.com/cc2qe/vawk)
GNU Parallel (http://www.gnu.org/software/parallel/)
mbuffer (http://www.maier-komor.de/mbuffer.html)
Ensembl Variant Effect Predictor (VEP) (http://www.ensembl.org/info/docs/tools/vep/index.html)
CNVnator (http://sv.gersteinlab.org/)
Install the ROOT package curl -OL ftp://root.cern.ch/root/root_v5.34.20.source.tar.gz tar -zxvf root_v5.34.20.source.tar.gz cd root ./configure --prefix=$PWD make
Source thisroot.sh source /pathto/root/bin/thisroot.sh
Compile CNVnator from the SpeedSeq directory cd $SPEEDSEQ_DIR make cnvnator
Before running SpeedSeq, you'll need to add the following line to speedseq.config or your .bashrc file. (Substitute the actual path to thisroot.sh on your system) source /pathto/root/bin/thisroot.sh
Install git clone --recursive https://github.com/hall-lab/speedseq cd speedseq make
Run the example script cd example ./run_speedseq This should produce the following files: example.bam example.discordants.bam example.splitters.bam example.vcf.gz example.sv.vcf.gz
As a template for installation on other systems, we have provided the exact commands for a full installation of SpeedSeq and GEMINI on a blank [Amazon Linux](Amazon Linux AMI 2014.09.2 (HVM)) box. These commands encompass all of the installation steps outlined below. System paths to SpeedSeq's component software are specified in the speedseq.config file, which should reside in the same directory as the SpeedSeq executable (for alternate locations use the -K flag). Upon installation, SpeedSeq attempts to automatically generate this file, but manual editing may be necessary. The core components enable standard functionality outlined in Quick start. Compilation requires g++ and the standard C and C++ development libraries. Additionally, cmake is required for building the BamTools API within FreeBayes and LUMPY. Essential SpeedSeq components can be installed with make, which produces a log file (install.log) that details the compilation status. The installation is modular, and its units can be built separately with make align, make var, make somatic, make sv, and make realign. This allows installation of only the desired components, eliminating extraneous dependencies. It further allows rebuilding of previously failed components. If any components already exist on the system or fail to install, their paths can be manually specified by editing speedseq.config. Optional components enable advanced features such as variant annotation and read-depth analysis. CNVnator requires the ROOT package as a prerequiste (https://root.cern.ch/drupal/). Please refer to the CNVnator repository for details on installing CNVnator.
Example SpeedSeq installation commands
g++ and the standard C and C++ development libraries (https://gcc.gnu.org/)
CMake (http://www.cmake.org/)
GNU awk and core utils
Python 2.7 (https://www.python.org/) numpy pysam 0.8.0+ scipy
ROOT (https://root.cern.ch/) (required if running CNVnator)
Variant Effect Predictor (http://www.ensembl.org/info/docs/tools/vep/index.html) (required if annotating VCF files)
BWA (http://bio-bwa.sourceforge.net/)
FreeBayes (https://github.com/ekg/freebayes)
LUMPY (https://github.com/arq5x/lumpy-sv)
Sambamba (http://lomereiter.github.io/sambamba/)
SAMBLASTER (https://github.com/GregoryFaust/samblaster)
Vawk (https://github.com/cc2qe/vawk)
GNU Parallel (http://www.gnu.org/software/parallel/)
mbuffer (http://www.maier-komor.de/mbuffer.html)
Ensembl Variant Effect Predictor (VEP) (http://www.ensembl.org/info/docs/tools/vep/index.html)
CNVnator (http://sv.gersteinlab.org/)
Install the ROOT package curl -OL ftp://root.cern.ch/root/root_v5.34.20.source.tar.gz tar -zxvf root_v5.34.20.source.tar.gz cd root ./configure --prefix=$PWD make
Source thisroot.sh source /pathto/root/bin/thisroot.sh
Compile CNVnator from the SpeedSeq directory cd $SPEEDSEQ_DIR make cnvnator
Before running SpeedSeq, you'll need to add the following line to speedseq.config or your .bashrc file. (Substitute the actual path to thisroot.sh on your system) source /pathto/root/bin/thisroot.sh
Support
Can I use SpeedSeq on exome data? SpeedSeq can detect SNVs and indels from exome data using speedseq var or speedseq somatic. However, you should not use the excluded regions, as these were designed for WGS data. SpeedSeq cannot detect SVs from exome data.
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