050114dragon / hrdecipher

calculate HRD score and visualise each scores on chromsomes

HRDecipher

Table of Contents

1. [Introduction] (#introduction)
2. [Installation] (#installation)
3. [Usage] (#usage)

Introduction

HRDecipher is a simple Python script that computes HRD genomic scars and plot each scar on chromosomes.

Installation

HRDecipher can be installed via git

git clone https://github.com/ZKai0801/HRDecipher.git

Python package pandas is required:

pip install pandas

R package argparse and karyoploteR is also required to visualise genomic scars

install.packages('argparse');

if (!requireNamespace("BiocManager", quietly = TRUE))
    install.packages("BiocManager")
BiocManager::install("karyoploteR")

Usage

[kai@admin HRDecipher]$ python3 HRDecipher.py -h
usage: HRDecipher.py [-h] [-o OUTPUT] input

positional arguments:
  input                 sampleID.pre_hrd.tsv, must contain following columns:
                        Chromosome, Start_position, End_position, total_cn,
                        A_cn, B_cn, ploidy

optional arguments:
  -h, --help            show this help message and exit
  -o OUTPUT, --output OUTPUT
                        Output file prefix

Sequenza is by far the most popular CNV caller that used in HRD calculation. But of course, any CNV callers that incorporates celluarity and ploidy calculation will do.

Here is an example pipeline: Sequenza_HRD.sh

Beware that although NGS data from many targeted-sequencing panels can be used to calculate HRD scars, ideally only WES/WGS data or panels that specifically designed that uniformly enriched on heterozygous sites (similar with SNP-array technology) are suitable for this aim.