This repository contains code and data resources to accompany our research paper:
Klimkowski Arango, N. & Morgante, F. (2024). Comparing statistical learning methods for complex trait prediction from gene expression. bioRxiv 2024.06.01.596951. https://doi.org/10.1101/2024.06.01.596951
Welcome! A brief overview of this repository can be found below
- snakefiles subdirectory contains all pipeline snakefiles
- other subdirectories contain scripts specific to pipeline
- this folder is the core for all pipelines
- data subfolder contains intermediate files for pipelines, procedurally generates by running smake.sbatch
- slurm subfolder contains config file specific to computing cluster
- log subfolder contains output/error messages from all rules
- figures and csv tables for use in publication
- important: set working directory and output directory within script
- safe-mode debug tool for job submissions
- allows prior confirmation that snakemake will run proper rules without overwriting existing files
- select snakefile within script to confirm pipeline
- important: set working directory and output directory within script
- job submitter for pipeline
- select snakefile within script to confirm pipeline
A workflowr site providing additional detail can be found here.
A workflowr project.