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Related Experiment Video

Updated: Jun 10, 2026

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

A Pathway Association Study Tool for GWAS Analyses of Metabolic Pathway Information

Published on: July 1, 2020

Pathway analysis software: annotation errors and solutions.

Nicole K Henderson-Maclennan¹, Jeanette C Papp, C Conover Talbot

¹Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA 90095-7088, USA.

Molecular Genetics and Metabolism

|July 29, 2010

Summary

This summary is machine-generated.

Annotation errors in genetic databases and bioinformatics tools can impact research. This study found pathway analysis software results vary with gene symbol annotations and input data types, suggesting improvements for data accuracy.

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Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

Genetic databases suffer from annotation errors, often undetected in large datasets.
Bioinformatics tools used for data interpretation may introduce or propagate these errors.
Accurate gene symbol annotations are critical for reliable biological conclusions.

Purpose of the Study:

To evaluate gene symbol annotation accuracy in commercial pathway analysis software (PAS).
To compare pathway analysis results across different software, time points, and input identifier types.
To identify factors affecting the reliability of PAS in genomic research.

Main Methods:

Analysis of gene symbol annotations from three commercial PAS packages (Ingenuity Pathways Analysis, GeneGO, Pathway Studio).
Comparison of canonical pathway results based on varying annotations and input data (e.g., microarray probe sets, RefSeq, GenBank, Entrez Gene IDs).
Assessment of annotation consistency across software versions and ID types.

Main Results:

Pathway analysis software results are influenced by variations in gene symbol annotations.
Differences in annotations exist across software releases and with different input identifier types.
Input data type significantly affects the consistency and accuracy of pathway analysis outcomes.

Conclusions:

Commercial pathway analysis software results are sensitive to gene symbol annotation quality and input ID type.
Recommendations are provided for enhancing the quality of microarray data reporting and PAS usage.
A collaborative platform (wiki) is proposed to address and communicate bioinformatics software issues.