Manta calls structural variants (SVs) and indels from mapped paired-end sequencing reads. It is optimized for analysis of germline variation in small sets of individuals and somatic variation in tumor/normal sample pairs. Manta discovers, assembles and scores large-scale SVs, medium-sized indels and large insertions within a single efficient workflow. The method is designed for rapid analysis on standard compute hardware: NA12878 at 50x genomic coverage is analyzed in less than 20 minutes on a 20 core server, and most WGS tumor/normal analyses can be completed within 2 hours. Manta combines paired and split-read evidence during SV discovery and scoring to improve accuracy, but does not require split-reads or successful breakpoint assemblies to report a variant in cases where there is strong evidence otherwise. It provides scoring models for germline variants in small sets of diploid samples and somatic variants in matched tumor/normal sample pairs. There is experimental support for analysis of unmatched tumor samples as well. Manta accepts input read mappings from BAM or CRAM files and reports all SV and indel inferences in VCF 4.1 format. See the [user guide] UserGuide for a full description of capabilities and limitations, and the [Manta preprint] mss for additional methods and benchmarking details.

Manta source code is provided under the [GPLv3 license] (LICENSE.txt). Manta includes several third party packages provided under other open source licenses, please see [COPYRIGHT.txt] (COPYRIGHT.txt) for additional details.

[![Build Status] tcistatus] tcihome

It is recommended to start from one of the [binary distributions on the Manta releases page] releases if a suitable version is available (note that the CentOS 5 binary distribution is expected to support a large variety of linux systems). If building from source start from the release distributions of the source code, also provided on the [Manta releases page] releases. Cloning/archiving the source directly from git could result in missing version number entries, undesirably stringent build requirements or an unstable development version between releases. Additional build notes for Manta developers can be found in the [manta developer guide] DeveloperGuide

Note that this README is NOT part of a tagged source-code release.

Manta requires a compiler supporting most of the C++11 standard. These are the current minimum versions enforced by the build system:

• python 2.4+
• gcc 4.7+ OR clang 3.1+ (OR Visual Studio 2013+, see windows note below)

• python 2.4+

Manta is known to build and run on the following linux distributions (with additional packages as described below):

• Ubuntu 12.04,14.04
• CentOS 5,6,7

Manta builds and passes basic tests on OS X 10.9, but full WGS analyses are not tested for this platform.

Manta does not build or run on windows. Library-level compilation is possible for Visual Studio users. See the the [manta developer guide] DeveloperGuide for details.

apt-get update -qq
apt-get install -qq gcc g++ make python

apt-get update -qq
apt-get install -qq bzip2 gcc g++ make python python-software-properties
# add gcc 4.8 from ubuntu ppa:
add-apt-repository -y ppa:ubuntu-toolchain-r/test
apt-get update -qq
apt-get install -qq gcc-4.8 g++-4.8

# Prior to build configuration, set CC/CXX to gcc 4.8:
export CC=/usr/bin/gcc-4.8
export CXX=/usr/bin/g++-4.8

yum install -y tar bzip2 make gcc gcc-c++

yum install -y tar wget bzip2 make gcc gcc-c++
# add gcc 4.8 from developer tools v2:
wget http://people.centos.org/tru/devtools-2/devtools-2.repo -O /etc/yum.repos.d/devtools-2.repo
yum install -y devtoolset-2-gcc devtoolset-2-gcc-c++ devtoolset-2-binutils

# Prior to build configuration, set CC/CXX to gcc 4.8:
export CC=/opt/rh/devtoolset-2/root/usr/bin/gcc
export CXX=/opt/rh/devtoolset-2/root/usr/bin/g++

After acquiring a release distribution of the source code, the build procedure is:

• Unpack source code
• Create and move to a separate build directory (out-of-source build is required.)
• Configure build
• Compile & Install

Example (building on 4 cores):

wget https://github.com/Illumina/manta/releases/download/v${MANTA_VERSION}/manta-${MANTA_VERSION}.release_src.tar.bz2
tar -xjf manta-${MANTA_VERSION}.release_src.tar.bz2
mkdir build && cd build
# Ensure that CC and CXX are updated to target compiler if needed, e.g.:
#     export CC=/path/to/cc
#     export CXX=/path/to/c++
../manta-${MANTA_VERSION}.release_src/src/configure --jobs=4 --prefix=/path/to/install
make -j4 install

Note that during the configuration step, the following dependencies will be built from source if they are not found:

• cmake 2.8.0+
• boost 1.56.0+

To accelerate this process the configuration step can be parallelized over multiple cores, as demonstrated in the example above with the --jobs=4 argument to configure.

To see more configure options, run:

${MANTA_SRC_PATH}/configure --help

After Manta is built the installation directory can be relocated to another directory. All internal paths used in the workflow are relative.

To help verify a successful installation, Manta includes a small demo data set and test script. After completing the installation steps above, the demo can be run as follows:

python ${MANTA_INSTALL_PATH}/bin/runMantaWorkflowDemo.py

See the demo README for additional information on the test script and data.

After completing installation, see the [Manta user guide] UserGuide for instructions on how to run Manta, interpret results, and a high-level overview of the method.

The user guide is also available within any Manta binary distribution here:

${MANTA_INSTALL_PATH}/doc/html/mantaUserGuide.html

Manta workflows are parallelized at the process level using the [pyFlow] pyflow_site task manager. pyFlow can distrubute Manta workflows to a specified number of cores on a single host or SGE-managed cluster.

As a useful runtime benchmark, [Platinum Genomes] PG sequencing reads for NA12878 at 50x coverage (whole genome) can be analyzed in less than 20 minutes on 20 physical cores using a dual Xeon E5-2680 v2 server with the BAM accessed from a conventional local drive, peak total memory (RSS) for this run was 2.35 Gb. Additional hardware notes:

• Memory Typical memory requirements are <1Gb/core for germline analysis and <2Gb/core for cancer/FFPE/highly rearranged samples. The exact requirement depends on many factors including sequencing depth, read length, fragment size and sample quality.

• CPU Manta does not require or benefit from any specific modern CPU feature (e.g. NUMA, AVX..), but in general faster clock and larger caches will improve performance.

• I/O I/O can be roughly approximated as 1.1 reads of the input alignment file per analysis, with no writes that are significant relative to the alignment file size.

For manta code development and debugging details, please see the [Manta developer guide] DeveloperGuide. This includes details on Manta's developement protocols, recommended workflows for debugging/investigating suspected FP or FN SV calls, and internal documentation details.