This repository contains code for processing of sequencing data and virus predictions, and data analysis used to generate results in Istvan et al. For details on this analysis see the preprint at medRxiv.
The input files for the pipeline are
- VirSorter output files (from sample-based assembly)
- Contig statistics
- Paired end reads passing QC
- A file with a list of sample names corresponding to the preceding files.
The bioinformatic analyses are written for the Linux OS as a Snakemake pipeline, and are intended to be run on an HPC cluster system. Software dependencies provided in conda environment specification files in workflow/envs/.
A more user-friendly version of this pipeline derived from the current pipeline is available as VirMake.
R scripts for analysis of data are available in analyses/. Required R packages include tidyverse, vegan, ape, gridExtra, broom, effectsize, ggrepel, UpSetR, and MaAsLin2.
To test the scripts, datasets and scripts are available for the generation of 1000 mock samples including information on a subset of the viral genomes identified in the study. Datasets required for running the mock analysis is available in the folder mock/from_real_data. To run the a mock analysis, run the script called analyses/scripts/for_manuscript/run_mock_analysis.R. The working directory for the script should be the repository folder. Running the mock datasets should take less than one hour on a regular desktop computer and will result in generation of statsitical tests, figures and tables reported in the manuscript, albeit with limited associations due to the random generation of input data.
This project is licensed under the MIT License - see the LICENSE file for details.