ReadsToRefs

A workflow for competitive alignment of ONT reads against a set of predefined references.

This workflow was initially designed to analyze sequencing data collected during a collaborative project between CSU and the USDA; however, it can (in theory) be adapted to a variety of use cases.

Currently, it is designed to:

1. Perform quality filtering, remove host reads, subsample (optional), and trim adapters.
2. Competitively align reads against a set of provided references.
3. Output a handful of files, including: alignment_heatmap_counts_top.png, alignment_heatmap_pct_top.png, alignment_summary_percentages.tsv, and parental_origin_annotated.tsv

The workflow assumes the following:

1. A data directory containing raw fastq.gz reads.
2. A references directory with a host.fasta and any number (>2) of target reference.fasta files. Theses files must be provided by the user.

3. Note: A sispa_primers.fasta file (located in /references) is needed for this particular workflow as there is a step that attempts to detect artifacts from library prep using SISPA + ONT.

Suggested usage:

1. Clone this repo to your desired workspace.
2. Create conda environment using provided environment.yml file.
3. Adjust desired presets in config.yaml
4. Activate workflow via snakemake --cores [INT]