Robust rank aggregation for gene list integration and meta-analysis
Quretec (Estonia) · University of Tartu
Abstract
MOTIVATION: The continued progress in developing technological platforms, availability of many published experimental datasets, as well as different statistical methods to analyze those data have allowed approaching the same research question using various methods simultaneously. To get the best out of all these alternatives, we need to integrate their results in an unbiased manner. Prioritized gene lists are a common result presentation method in genomic data analysis applications. Thus, the rank aggregation methods can become a useful and general solution for the integration task. RESULTS: Standard rank aggregation methods are often ill-suited for biological settings where the gene lists are inherently…
Citation impact
- FWCI
- 8.46
- Percentile
- 100%
- References
- 29
Authors
4Topics & keywords
- Computer science
- Data mining
- Outlier
- Rank (graph theory)
- Probabilistic logic
- Uncorrelated
- Noise (video)
- Statistical hypothesis testing
- Industry, innovation and infrastructure