MCPyViewer

This repo includes scripts to visualize the contig at virus integration from SearchMCPV - edit this part

If you use the MCPyViewer visualization tool, please cite our manuscript: Add citation

searchMCPV

A MCPV integration point detection tool for targeted capture sequencing data. Details on how to run this tool are described here : https://github.com/WenjinGudaisy/SearcHPV

• update to refelct MCPV genome (Ask Wenjin)

Getting started

1. Required resources

   • Unix like environment

2. Download and install the required resources

   • Download conda >=22.9.0: https://docs.conda.io/projects/conda/en/latest/user-guide/install/linux.html#install-linux-silent

   • Download the "environment.yaml" file under this repository

   • Create conda environment for MCPyViewer:

     conda env create -f [your_path]/environment.yaml
     
     This command will automatically set up all the third-party tools and packages required for MCPyViewer. The name of the environment is "MCPV_analysis_toolkit" (edit later as needed).
     
     You can check the packages and tools in this environment by:
     
       conda list -n MCPV_analysis_toolkit
     
     You can update the environment by:
     
       conda env update -f [your_path]/environment.yaml
     

3. Usage - Activate the conda environment

       conda activate MCPV_analysis_toolkit
   

Generate MCPV link plots

Pipeline to generate link plot of viral integration breakpoints within the human and MCPyV genomes and plot showing the distribution of degree of microhomology at breakpoints of MCPyV integrations (shown in Figure 3 (A,B))

./MCPV_link_plot.sh -w {workdir} -i samples.txt -o intermediate_files/

Example samples.txt file : Sample tumor1 tumor2 tumor3 . . tumorN

     Outputs are stored in a directory called "MCV_link_plots"