pylmm is a fast and lightweight linear mixed-model (LMM) solver for use in genome-wide association studies (GWAS). The original is derived from FaST-LMM and that code base can be found here.
This is an improved and faster version of pylmm which is part of the Genenetwork2 project.
This edition of pylmm has been tested on Python 2.7.3. Dependencies for single and multi-core use are
numpy
scipy
For CUDA dependencies are (in addition to a functional NVIDIA Tesla installation)
pycuda
scikits.cuda
You may need to add something like
export CUDA_ROOT=/usr/local/cuda-7.0
export PATH=$CUDA_ROOT/bin:$PATH
export LD_LIBRARY_PATH=$CUDA_ROOT/lib64
Test CUDA support with
./bin/cuda_properties.py
By default pylmm finds CUDA and runs on the GPU. If there is no CUDA support multi-core numpy is used. To avoid CUDA use --no-cuda. To force BLAS use the --blas switch.
Pjotr Prins
pylmm is offered under the GNU Affero GPL (https://www.gnu.org/licenses/why-affero-gpl.html). See also LICENSE.txt file that comes with the source.