Sentence examples for sample predictors from inspiring English sources

The third, class discovery, is an unbiased approach based either on unsupervised hierarchical clustering or centroids (single sample predictors (SSPs)).

The agreement between methods on how to classify individual tumors are not optimal and how to establish more robust single sample predictors is actively debated [ 8- 11].

This was very clearly confirmed by Weigelt and colleagues [ 6] in a recent study (2010) comparing the relative efficiency of two single sample predictors (SSPs).

In summary, the molecular subtyping of breast cancers based on their transcriptome varies with the intrinsic gene list or with the single sample predictors used for the classification (Weigelt et al., 2010).

The observation of more stable classification for Basal-like breast cancers coincides with the recent observation that Basal-like breast cancers are more robustly identified (relative to other subtypes) in single sample predictors[ 26].

Therefore, 'single sample predictors' (SSPs) were developed on the basis of the correlation between the expression profile of a given sample with the centroids for each molecular subtype (that is, average expression profile of each molecular subtype) [ 13, 17, 26].

The form recorded citation, description and size of sample, predictors examined and measurement properties (i.e., validity and reliability, when available), covariates examined, and effect size (for those with the exposure and those without).

Although there is some consistency in the recognition of these differing subgroups between GEP studies, there is some doubt as to the stability of the classifiers used by different single sample predictors (Weigelt et al, 2010b) and most assays are not yet ready for routine clinical use (De Ronde et al, 2010).