A Simple Python Wrapper for IMPUTE2 — [Bioinformatics Eps.5]
IMPUTE2 is a powerful genotype imputation and haplotype phasing program based on ideas from Howie et al. 2009. It has become an essential tool in the analysis of genetic data, offering high accuracy and fast imputation. In this blog post, we will present a simple Python wrapper for running IMPUTE2 and calculating SNP data based on the analysis. This script is designed to work on Linux, as the IMPUTE2 executable is built for Linux systems. For more information about IMPUTE2, you can visit the official website: https://mathgen.stats.ox.ac.uk/impute/impute_v2.html.
In this blog post, we’ll explore a Python script that can be used to run IMPUTE2 analysis on a given input file, and calculate the number of SNPs that have been successfully imputed with good quality.
The Python wrapper consists of several functions that work together to run IMPUTE2 and calculate the SNP data from the analysis. We will break down the script into its main components:
input_checker(): This function checks the input file provided by the user to ensure it exists before passing it to the IMPUTE2 process. If the input file is not found, an exception will be raised.
The Python script uses the argparse module to allow the user to specify the input file for IMPUTE2 analysis, as well as the output file from the analysis. If no input file is specified, the script will use a default input file located in the “Example” directory.
run_impute2(): This function runs the IMPUTE2 process using the input and output file paths provided by the user. If there is an issue running the process, an exception will be raised, and an error message will be printed.
The run_impute2() function is responsible for running the IMPUTE2 analysis using the input file and output file specified by the user. The function uses the os.system() method to execute the IMPUTE2 command line tool with the necessary input files and parameters. The output of the analysis is saved in a file specified by the user, and any error that occurs during the analysis is caught and displayed as an error message.
calculate_snp(): This function calculates various SNP-related metrics from the input and output data files. It uses thecsvlibrary to read the data from the files efficiently. The metrics calculated include:
- Individuals in the Study Dataset
- Haplotype from the reference panel
- SNPs in the Study Dataset
- SNPs in the Output of the analysis
- SNPs that have been imputed with good quality
main(): This is the main function that brings everything together. It sets up the command-line argument parser, runs the IMPUTE2 process, and calculates the SNP metrics.
To run the script, simply execute it from the command line using the following com
python3 snp.py -i input_file_path -o output_file_pathReplace input_file_path and output_file_path with the paths to your input and output files, respectively. If everything runs successfully, you will see the IMPUTE2 process running and the calculated SNP metrics printed to the console.
For the full code and documentation check it here
In conclusion, the Python script provided in this blog post allows the user to run IMPUTE2 analysis on a given input file and calculate the number of successfully imputed SNPs with good quality. By automating this process with Python, users can save time and simplify their workflow for genotype imputation.
Remember to always follow best practices and optimize your code for your specific use case. With the right tools and techniques, you can unlock the full potential of IMPUTE2 and make significant contributions to the field of genetics.
