Skip to content

MarraLab/callHPVIntegrationShortReadWGS

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

15 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Calling HPV Integration Using Illumina Short-Read Sequencing

Workflow for calling HPV integration sites and events in Illumina short-read sequencing data.

Installation

This will clone the repository. You can run workflow within this directory.

git clone https://github.com/vanessa-porter/illuminaCallHPVInt

Dependencies

To run this workflow, you must have snakemake (v6.12.3) and conda. You can install snakemake using this guide. The remaining dependencies will be downloaded automatically within the snakemake workflow.

Input Files

Method 1: Whole genome

  • WGS alignment (bam file)

Method 2: RNA-seq

  • RNA alignment (bam file)
  • Use RNA branch for RNA-seq for now

Set Up Configuration Files

Edit the config files

Example parameters.yaml:

Config files to specify parameters and paths needed for the workflow. The main parameter to include is the genome path.

genome_path: /path/to/genome/fasta

Example samples.yaml:

Main config file to specify input files.

bams:
    sampleName_1: /path/to/bam/file
    sampleName_2: /path/to/bam/file

Converting sample paths to yaml file

A text file can be converted to the samples.yaml file using the scripts/sampletsvtoyaml.py script. The tsv file should have the sample name in one column and the path in another and be tab delimited (no header).

scripts/sampletsvtoyaml.py -t samples.txt -o config/samples.yaml

Run Workflow

This is the command to run the workflow with snakemake using conda. The -c parameter can be used to specify maximum number of threads.

snakemake -c 30 --use-conda

Contributors

The contributors of this project are Vanessa Porter

About

Workflow for calling HPV integration sites and events in Illumina short-read sequencing data.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages

  • Python 53.2%
  • R 46.8%