NCBI-Hackathons / Scan2CNV

MIT License
1 stars 0 forks source link

alt text

Synopsis

This program is designed to generate CNV calls from raw SNP array data using the command line.

Workflow

alt text

Installation

Clone the repository

git clone --recursive https://github.com/NCBI-Hackathons/Global_Screening_Arrays.git

Usage

./Scan2CNV.py -h
usage: Scan2CNV.py [-h] -n NAME_OF_PROJECT -g PATH_TO_GTC_DIRECTORY -d
                   DIRECTORY_FOR_OUTPUT -b BPM_FILE [-p PFB_FILE] [-hmm HMM]
                   [-m] [-q QUEUE] [-u]

optional arguments:
  -h, --help            show this help message and exit
  -p PFB_FILE, --pfb_file PFB_FILE
                        Path to PennCNV PFB file. REQUIRED for CNV calling.
                        Use -m option to create.
  -hmm HMM, --hmm HMM   Path to PennCNV hmm file. Should be included with
                        PennCnv download.
  -m, --make_pfb        use flag to indicate to generate PFB file
  -q QUEUE, --queue QUEUE
                        OPTIONAL. Queue on cluster to use to submit jobs.
                        Defaults to all of the seq queues and all.q if not
                        supplied. default="all.q"
  -u, --unlock_snakemake
                        OPTIONAL. If pipeline was killed unexpectedly you may
                        need this flag to rerun

Required Arguments:
  -n NAME_OF_PROJECT, --name_of_project NAME_OF_PROJECT
                        Name to give to project for some output files
  -g PATH_TO_GTC_DIRECTORY, --path_to_gtc_directory PATH_TO_GTC_DIRECTORY
                        Full path to directory containing gtc files. It will
                        do a recursive search for gtc files.
  -d DIRECTORY_FOR_OUTPUT, --directory_for_output DIRECTORY_FOR_OUTPUT
                        REQUIRED. Full path to the base directory for the
                        ArrayScan2CNV pipeline output
  -b BPM_FILE, --bpm_file BPM_FILE
                        REQUIRED. Full path to Illumina .bpm manifest file.

Dependencies

R packages: gsrc v1.1

Python modules: PennCNV v1.0.3

Software: python v2.7.5, R v3.3.1