  Non-sharable sensitive data collection and analysis in large-scale consortia
for genomic research is complicated. Time consuming issues in installing
software arise due to different operating systems, software dependencies and
running the software. Therefore, easier, more standardized, automated protocols
and platforms can be a solution to overcome these issues. We have developed one
such solution for genomic data analysis using software container technologies.
The platform, COGEDAP, consists of different software tools placed into
Singularity containers with corresponding pipelines and instructions on how to
perform genome-wide association studies (GWAS) and other genomic data analysis
via corresponding tools. Using a provided helper script written in Python,
users can obtain auto-generated scripts to conduct the desired analysis both on
high-performance computing (HPC) systems and on personal computers. The
analyses can be done by running these auto-generated scripts with the software
containers. The helper script also performs minor re-formatting of the
input/output data, so that the end user can work with a unified file format
regardless of which genetic software is used for the analysis. COGEDAP is
actively being used by users from different countries/projects to conduct their
genomic data analyses. Thanks to this platform, users can easily run GWAS and
other genomic analyses without spending much effort on software installation,
data formats, and other technical requirements.
