# PySmooth: a Python tool for the removal and correction of genotyping errors

**Authors:** Benjamin Soibam, Gregg Roman

PMC · DOI: 10.1186/s13104-024-06753-4 · 2024-04-11

## TL;DR

PySmooth is a Python tool that helps correct genotyping errors in genetic studies, improving the accuracy of SNP data for disease research.

## Contribution

PySmooth introduces an improved, user-friendly tool for correcting genotyping errors with enhanced features like missing data imputation and visualization.

## Key findings

- PySmooth builds on the SMOOTH tool with modifications for better usability and functionality.
- The tool can detect and correct genotyping errors while also imputing missing data.
- PySmooth supports flexible parameters and handles a wider range of genotype codes.

## Abstract

In genetic mapping studies involving many individuals, genome-wide markers such as single nucleotide polymorphisms (SNPs) can be detected using different methods. However, it comes with some errors. Some SNPs associated with diseases can be in regions encoding long noncoding RNAs (lncRNAs). Therefore, identifying the errors in genotype file and correcting them is crucial for accurate genetic mapping studies. We develop a Python tool called PySmooth, that offers an easy-to-use command line interface for the removal and correction of genotyping errors. PySmooth uses the approach of a previous tool called SMOOTH with some modifications. It inputs a genotype file, detects errors and corrects them. PySmooth provides additional features such as imputing missing data, better user-friendly usage, generates summary and visualization files, has flexible parameters, and handles more genotype codes.

PySmooth is available at https://github.com/lncRNAAddict/PySmooth.

The online version contains supplementary material available at 10.1186/s13104-024-06753-4.

## Full-text entities

- **Chemicals:** NA (MESH:D012964), SMOOTH (-)

## Figures

2 figures with captions in the complete paper: https://tomesphere.com/paper/PMC11010338/full.md

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Source: https://tomesphere.com/paper/PMC11010338