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Genetic Screens

Genetic Screens

Genetic screens are tools used to identify genes and mutations responsible for phenotypes of interest. Genetic screens help identify individuals or a group of people at risk of developing genetic diseases and help them with early intervention, targeted therapy, and reproductive options.
Forward genetic screens
Forward or “classical” genetic screens involve creating random mutations in an organism’s DNA using radiation, mutagens, or insertion of additional bases, which...

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Updated: Jul 5, 2025

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Published on: April 4, 2018

PaintorPipe: a pipeline for genetic variant fine-mapping using functional annotations.

Zoé Gerber^1,2, Michel Fisun³, Hugues Aschard^3,4

¹IRSD, Université de Toulouse, INSERM, INRAE, ENVT, Université Toulouse III - Paul Sabatier (UPS), 31024 Toulouse, France.

Bioinformatics Advances

|January 12, 2024

Summary

This summary is machine-generated.

PaintorPipe is a new Nextflow pipeline that simplifies the process of identifying causal genetic variants associated with diseases using genome-wide association studies (GWAS) data and functional annotations.

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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

Published on: May 22, 2018

Area of Science:

Genetics
Bioinformatics
Computational Biology

Background:

Genome-wide association studies (GWAS) identify numerous genetic variants linked to common diseases.
These variants are often in linkage disequilibrium (LD), making it challenging to pinpoint causal variants.
Existing fine-mapping methods require extensive pre- and post-processing steps.

Purpose of the Study:

To develop a streamlined Nextflow pipeline, PaintorPipe, for efficient genetic fine-mapping.
To integrate GWAS summary statistics, LD information, and functional annotations for variant prioritization.
To simplify the application of the PAINTOR framework for Bayesian fine-mapping.

Main Methods:

PaintorPipe automates pre- and post-processing for the PAINTOR fine-mapping program.
It utilizes GWAS summary statistics, LD data, and functional annotations as input.
The pipeline performs Bayesian fine-mapping to calculate posterior probabilities for causal variants.

Main Results:

PaintorPipe successfully integrates diverse data sources for variant fine-mapping.
It automates complex computational steps, reducing user effort.
The pipeline generates ranked credible sets of variants annotated with biological functions.

Conclusions:

PaintorPipe offers a user-friendly and efficient solution for genetic fine-mapping.
It enhances the interpretability of GWAS results by identifying potential causal variants.
The pipeline facilitates the integration of functional genomics data in disease association studies.