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Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

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Related Experiment Video

Updated: Sep 18, 2025

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

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ProHap Explorer: Visualizing Haplotypes in Proteogenomic Datasets.

Jakub Vasicek, Dafni Skiadopoulou, Ksenia G Kuznetsova

IEEE Computer Graphics and Applications

|June 20, 2025

Summary

This summary is machine-generated.

ProHap Explorer visualizes how genetic variations (haplotypes) impact human proteins, revealing non-canonical peptides in mass spectrometry data. This tool aids personalized medicine by exploring proteogenomic variation.

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Last Updated: Sep 18, 2025

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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools

Published on: August 19, 2025

Area of Science:

Proteomics
Genomics
Bioinformatics

Background:

Mass spectrometry-based proteomics typically uses single reference sequences, ignoring haplotype influences.
Haplotypes, combinations of inherited genetic variants, can alter protein sequences and their detection.
Existing tools do not adequately visualize the impact of common haplotypes on proteomic data.

Purpose of the Study:

To introduce ProHap Explorer, a novel visualization interface for exploring haplotype effects on the human proteome.
To enable users to investigate how common haplotypes influence protein sequences and identify non-canonical peptides.
To support the analysis of proteogenomic variation in mass spectrometry datasets.

Main Methods:

Development of ProHap Explorer, a user-friendly interface for visualizing proteogenomic data.
Integration of established biological sequence analysis representations with interactive elements.
Testing and validation through user interviews with proteomics experts.

Main Results:

ProHap Explorer facilitates the exploration of haplotypes and their impact on protein sequences.
The tool aids in identifying non-canonical peptides in public mass spectrometry datasets.
User feedback confirmed the utility of ProHap Explorer in assessing haplotype effects on proteins of interest.

Conclusions:

ProHap Explorer provides an intuitive platform for exploring proteogenomic variation.
The tool enhances the understanding of haplotype influences in mass spectrometry-based proteomics.
ProHap Explorer supports advancements in personalized medicine and targeted therapy development.