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

dgrp-starve

Welcome! A brief overview of this repository can be found below

Important folders:

code

• snakefiles subdirectory contains all pipeline snakefiles
• other subdirectories contain scripts specific to pipeline

snake

• 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

output

• figures and csv tables for use in publication

Job submission:

snake.sbatch

• 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

smake.sbatch

• important: set working directory and output directory within script
• job submitter for pipeline
• select snakefile within script to confirm pipeline

workflowr

A workflowr site providing additional detail can be found here.

A workflowr project.