v1.8
This release introduces many improvements in the code and some new features.
Improvements
- refactor the code for multi-models execution: analysis runs are now managed using project meta-data channel without the need to spawn additional nextflow processes. This makes monitoring, execution and resuming easier to manage
groupKeyis now implemented to ensure each phenotype is analyzed independently without waiting for all processes to complete at each step before proceeding- phenotype and covariates validation are now performed with Python scripts, removing dependency on Java and jbang
- generation of HTML reports is now based on quarto with notebooks based on Python and the GWASLab packages. This reduces the amount of time and resources needed to generate the reports
- The docker container has been reorganized into one main container for analysis and one managing only the reports generation to be more flexible in case we want to improve the reports.
New features
- Easier to configure multi-models execution: now you can run multi-models using the same config file structure and adding the
models_tableparameters - Better HTML reports based on quarto and using the GWASLab python package. Reports now include regional plots for the top loci.
- A more organized workflow for multi-models execution that allows better control of the computational resources
- Better conversion of VCF / BCF to PGEN with more control on importing options
- Improved documentation on GitHub pages