Test set bias affects reproducibility of gene signatures.

ABSTRACT:

Motivation

Prior to applying genomic predictors to clinical samples, the genomic data must be properly normalized to ensure that the test set data are comparable to the data upon which the predictor was trained. The most effective normalization methods depend on data from multiple patients. From a biomedical perspective, this implies that predictions for a single patient may change depending on which other patient samples they are normalized with. This test set bias will occur when any cross-sample normalization is used before clinical prediction.

Results

We demonstrate that results from existing gene signatures which rely on normalizing test data may be irreproducible when the patient population changes composition or size using a set of curated, publicly available breast c

SUBMITTER: Patil P 

PROVIDER: S-EPMC4495301 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature