Pathway analysis software: Annotation errors and solutions
| Autor: | C. Conover Talbot, Edward R.B. McCabe, Jeanette C. Papp, Angela P. Presson, Nicole K. Henderson-MacLennan |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
Computer science
Endocrinology Diabetes and Metabolism media_common.quotation_subject Bioinformatics Biochemistry Article Set (abstract data type) User-Computer Interface Annotation Endocrinology Software Ingenuity Databases Genetic Genetics RefSeq Gene Symbol Molecular Biology Oligonucleotide Array Sequence Analysis media_common Internet Information retrieval business.industry Gene Expression Profiling Entrez Gene Computational Biology Identifier ComputingMethodologies_PATTERNRECOGNITION Genes business |
| Zdroj: | Molecular Genetics and Metabolism. 101:134-140 |
| ISSN: | 1096-7192 |
| DOI: | 10.1016/j.ymgme.2010.06.005 |
| Popis: | Genetic databases contain a variety of annotation errors that often go unnoticed due to the large size of modern genetic data sets. Interpretation of these data sets requires bioinformatics tools that may contribute to this problem. While providing gene symbol annotations for identifiers (IDs) such as microarray probe set, RefSeq, GenBank, and Entrez Gene is seemingly trivial, the accuracy is fundamental to any subsequent conclusions. We examine gene symbol annotations and results from three commercial pathway analysis software (PAS) packages: Ingenuity Pathways Analysis, GeneGO, and Pathway Studio. We compare gene symbol annotations and canonical pathway results over time and among different input ID types. We find that PAS results can be affected by variation in gene symbol annotations across software releases and the input ID type analyzed. As a result, we offer suggestions for using commercial PAS and reporting microarray results to improve research quality. We propose a wiki type website to facilitate communication of bioinformatics software problems within the scientific community. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect