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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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A Fast and Quantitative Method for Post-translational Modification and Variant Enabled Mapping of Peptides to Genomes

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SNPexp - A web tool for calculating and visualizing correlation between HapMap genotypes and gene expression levels.

Kristian Holm¹, Espen Melum, Andre Franke

¹Norwegian PSC Research Center, Clinic for Specialized Medicine and Surgery, Oslo University Hospital Rikshospitalet, Norway.

BMC Bioinformatics

|December 21, 2010

Summary

This summary is machine-generated.

SNPexp is a new web tool that analyzes the relationship between genetic variations (SNPs) and gene expression. It helps researchers visualize expression quantitative trait loci (eQTLs) for genetic studies.

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Area of Science:

Genomics
Bioinformatics
Systems Biology

Background:

Publicly available expression data for 47,294 transcripts and genotypes for 3.96 million single nucleotide polymorphisms (SNPs) from HapMap individuals.
Genomic and transcriptomic data offer opportunities for understanding genotype-phenotype correlations.

Purpose of the Study:

To develop a user-friendly web-based tool for visualizing the correlation between SNP genotypes and gene expression levels.
To facilitate expression quantitative trait locus (eQTL) analysis.

Main Methods:

SNPexp utilizes linear regression and the Wald test, implemented in PLINK.
Results are visualized using the UCSC Genome Browser.
The tool is implemented as a server-side script.

Main Results:

SNPexp successfully calculates and visualizes correlations between genotypes and transcript expression.
Validation using known eQTLs demonstrated comparable results to existing methods.
The tool supports analysis of both cis and trans regulatory effects.

Conclusions:

SNPexp offers a convenient, platform-independent method for eQTL analysis.
It serves as a valuable supplement to existing bioinformatics tools.
The tool is accessible via a website and can be used locally with custom datasets.