Empirical comparison of structure-based pathway methods
| Autor: | Maria K. Jaakkola, Laura L. Elo |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Proteome Empirical comparison Computer science 0206 medical engineering 02 engineering and technology Computational biology Multiple methods computer.software_genre Sensitivity and Specificity 03 medical and health sciences statistical analysis Protein Interaction Mapping Humans Molecular Biology Selection (genetic algorithm) Gene Expression Profiling ta111 Reproducibility of Results Pathway analysis Expression (mathematics) pathway analysis Gene expression profiling 030104 developmental biology pathway structure comparison Papers Structure based Cell cancer Data mining functional genomics computer Algorithms Metabolic Networks and Pathways Software 020602 bioinformatics Signal Transduction Information Systems |
| Zdroj: | Briefings in Bioinformatics |
| ISSN: | 1467-5463 |
| Popis: | Multiple methods have been proposed to estimate pathway activities from expression profiles, and yet, there is not enough information available about the performance of those methods. This makes selection of a suitable tool for pathway analysis difficult. Although methods based on simple gene lists have remained the most common approach, various methods that also consider pathway structure have emerged. To provide practical insight about the performance of both list-based and structure-based methods, we tested six different approaches to estimate pathway activities in two different case study settings of different characteristics. The first case study setting involved six renal cell cancer data sets, and the differences between expression profiles of case and control samples were relatively big. The second case study setting involved four type 1 diabetes data sets, and the profiles of case and control samples were more similar to each other. In general, there were marked differences in the outcomes of the different pathway tools even with the same input data. In the cancer studies, the results of a tested method were typically consistent across the different data sets, yet different between the methods. In the more challenging diabetes studies, almost all the tested methods detected as significant only few pathways if any. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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