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OmicABELnoMM implements a high-performance computing algorithm for linear regression of omics data

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Introduction

OmicABELnoMM is a tool for running Genome-Wide Association Studies (GWASn) on large multi-omics datasets in a computationally efficient manner. The tool is specifically designed to run linear regression on thousands of phenotypes (e.g. metabolomics data) for thousands of individuals and millions of (imputed) genotypes within a reasonable time frame (think days instead of months or years).

IMPORTANT NOTICE

Early 2018, PolyOmica, the main sponsor of the GenABEL project announced that it would discontinue its support. As PolyOmica was our only sponsor, we regretfully have to announce the likely discontinuation of the GenABEL Project in its current form, unless a new sponsor steps up or someone takes over maintenance and futher development of (some of) the tools.

Requirements

Hardware

OmicABELnoMM requires a modern high-end computer with a multi-core processor. Currently, OmicABELnoMM has experimental support for MPI, which means that the tasks can be distributed over different compute nodes in a cluster.

Software

OmicABELnoMM is designed to run on Linux (it won’t run on MS Windows; well, we actually never tested that). In terms of libraries, OmicABELnoMM depends on LAPACKe and a BLAS library. There are several choices for a BLAS library: OpenBLAS, AMD’s ACML or the Intel MKL. For the calculation of p-values OmicABEL depends on the Boost library.

If you would like to use/test the MPI functionality, you will need either the OpenMPI or the MPICH2 library.

Installation

Because OmicABELnoMM was designed and developed with High-Performance Computing (HPC) in mind, it works most efficiently when compiled from the source code, including the libraries it depends on, on the machine it will be run. This will allow the compiler to choose the most optimal settings that match your hardware (mainly the processor).

Unfortunately, the process of compiling from source, while not prohibitively complicated, is not trivial. As an alternative to compiling both OmicABELnoMM and its dependencies from source you can opt for installing existing packages provided in the repositories of your Linux distribution. However, this will come at a cost: performance will be lower than if you compile the package and its libraries for your own architecture.

Support

Community support for OmicABELnoMM can be found at the GenABEL forum. Feel free to ask your questions there and to contribute with your own knowledge and skills.

Commercial support for OmicABELnoMM can be obtained via PolyOmica. Typical things PolyOmica can help you with are installing OmicABELnoMM on your server or cluster, or the development of custom features.

Contributing

OmicABELnoMM is a free software project, we therefore welcome contributions of all kind. Development takes place on GitHub, where you will find the source code and the list of bugs. Feel free to submit your bug reports or feature requests there, or, even better, fork the project and start fixing those bugs. Development discussions take place on the GenABEL development mailing list. We are looking forward to working with you!

Licence

OmicABELnoMM is free software licensed under the GNU General Public License v3. A copy of the licence can be found in the file COPYING.

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OmicABELnoMM implements a high-performance computing algorithm for linear regression of omics data

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