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PLoS One. 2010 Nov 23;5(11):e15543. doi: 10.1371/journal.pone.0015543.

Nearest template prediction: a single-sample-based flexible class prediction with confidence assessment.

Author information

1
Cancer Program, Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, USA. hoshida@broadinstitute.org

Abstract

Gene-expression signature-based disease classification and clinical outcome prediction has not been widely introduced in clinical medicine as initially expected, mainly due to the lack of extensive validation needed for its clinical deployment. Obstacles include variable measurement in microarray assay, inconsistent assay platform, analytical requirement for comparable pair of training and test datasets, etc. Furthermore, as medical device helping clinical decision making, the prediction needs to be made for each single patient with a measure of its reliability. To address these issues, there is a need for flexible prediction method less sensitive to difference in experimental and analytical conditions, applicable to each single patient, and providing measure of prediction confidence. The nearest template prediction (NTP) method provides a convenient way to make class prediction with assessment of prediction confidence computed in each single patient's gene-expression data using only a list of signature genes and a test dataset. We demonstrate that the method can be flexibly applied to cross-platform, cross-species, and multiclass predictions without any optimization of analysis parameters.

PMID:
21124904
PMCID:
PMC2990751
DOI:
10.1371/journal.pone.0015543
[Indexed for MEDLINE]
Free PMC Article

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