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# INSTALL GEMMA: Genome-wide Efficient Mixed Model Association
## Check version
Simply run gemma once installed
gemma
and it should give you the version.
## GEMMA dependencies
GEMMA runs on Linux and MAC OSX and the runtime has the following
dependencies:
* C++ tool chain >= 4.9
* GNU Science library (GSL) 1.x (note that 2.x is not yet supported)
* blas/openblas
* lapack
* [Eigen3 library](http://eigen.tuxfamily.org/dox/)
* zlib
See below for installation on Guix.
## Install GEMMA
### Debian and Ubuntu
Travis-CI uses Ubuntu for testing. Check the test logs for version numbers.
[](https://travis-ci.org/genetics-statistics/GEMMA)
Current settings can be found in [travis.yml](.travis.yml).
### Bioconda
(Note Bioconda install is a work in [progress](https://github.com/genetics-statistics/GEMMA/issues/52)
Recent versions of GEMMA can be installed with
[BioConda](http://ddocent.com/bioconda/) without root permissions using the following
command
conda install gemma
### GNU Guix
The GNU Guix package manager can install recent versions of [GEMMA](https://www.gnu.org/software/guix/packages/g.html)
using the following command
guix package -i gemma
To build GEMMA from source you can opt to install the build tools with GNU Guix
guix package -i make gcc linux-libre-headers gsl eigen openblas lapack glibc ld-wrapper
### Install from source
Install listed dependencies and run
make -j 4
(the -j switch builds on 4 cores).
if you get an Eigen error you may need to override the include
path. E.g. to build GEMMA on GNU Guix with shared libs the following
may work
make EIGEN_INCLUDE_PATH=~/.guix-profile/include/eigen3 WITH_OPENBLAS=1
another example overriding optimization and LIB flags (so as to link
against gslv1) would be
make EIGEN_INCLUDE_PATH=~/.guix-profile/include/eigen3 WITH_OPENBLAS=1 GCC_FLAGS="-Wall" LIBS="$HOME/opt/gsl1/lib/libgsl.a $HOME/opt/gsl1/lib/libgslcblas.a -L$HOME/.guix-profile/lib -pthread -llapack -lblas -lz"
to run GEMMA tests
time make check
You can run gemma in the debugger with, for example
gdb --args \
./bin/gemma -g example/mouse_hs1940.geno.txt.gz \
-p example/mouse_hs1940.pheno.txt -a example/mouse_hs1940.anno.txt \
-snps example/snps.txt -nind 400 -loco 1 -gk -debug -o myoutput
Note that if you get <optimized out> warnings on inspecting variables you
should compile with GCC_FLAGS="" to disable optimizations (-O3). E.g.
make EIGEN_INCLUDE_PATH=~/.guix-profile/include/eigen3 WITH_OPENBLAS=1 GCC_FLAGS=
Other options, such as compiling with warnings, are listed in the
Makefile.
## Run tests
GEMMA includes the shunit2 test framework (version 2.0).
make check
or
./run_tests.sh
## Optimizing performance
### OpenBlas
Linking against a built-from-source OpenBlas is a first optimization
step because it will optimize code for the local architecture (on my
workstation it easily doubles speed). When you check the output .log
file of GEMMA after a run, it will tell you how the linked-in OpenBlas
was compiled.
To link a new version, compile OpenBlas as per
[instructions](http://www.openblas.net/). You can start with the default:
make -j 4
or play with the switches
make USE_THREAD=1 NUM_THREADS=16 -j 4
rendering for example:
OpenBLAS build complete. (BLAS CBLAS)
OS ... Linux
Architecture ... x86_64
BINARY ... 64bit
C compiler ... GCC (command line : gcc)
Library Name ... libopenblas_haswellp-r0.3.0.dev.a (Multi threaded; Max num-threads is 16)
To install the library, you can run "make PREFIX=/path/to/your/installation install".
This generates a static library which you can link using the full path
with using the GEMMA Makefile:
time env OPENBLAS_NUM_THREADS=4 make EIGEN_INCLUDE_PATH=~/.guix-profile/include/eigen3 LIBS="~/tmp/OpenBLAS/libopenblas_haswellp-r0.3.0.dev.a -lgsl -lgslcblas -pthread -lz -llapack" WITH_OPENBLAS=1 -j 4 fast-check
make EIGEN_INCLUDE_PATH=~/.guix-profile/include/eigen3 LIBS="~/tmp/OpenBLAS/libopenblas_haswellp-r0.3.0.dev.a -lgsl -lgslcblas -pthread -lz -llapack" WITH_OPENBLAS=1 -j 4 unittests
NOTE: we should make this easier.
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