QiSampler: evaluation of scoring schemes for high-throughput datasets using a repetitive sampling strategy on gold standards.

ABSTRACT:

Background

High-throughput biological experiments can produce a large amount of data showing little overlap with current knowledge. This may be a problem when evaluating alternative scoring mechanisms for such data according to a gold standard dataset because standard statistical tests may not be appropriate.

Findings

To address this problem we have implemented the QiSampler tool that uses a repetitive sampling strategy to evaluate several scoring schemes or experimental parameters for any type of high-throughput data given a gold standard. We provide two example applications of the tool: selection of the best scoring scheme for a high-throughput protein-protein interaction dataset by comparison to a dataset derived from the literature, and evaluation of functional enrichmen

SUBMITTER: Fontaine JF 

PROVIDER: S-EPMC3060832 | biostudies-literature | 2011 Mar

REPOSITORIES: biostudies-literature