Latent Effect Adjustment After Primary Projection
Alternating singular value decomposition
Compute the area under the ROC curve (AUC)
Compute the false positive rate at given sizes of retrieved genes
compute the precision at given sizes of retrieved genes
compute the recall at given sizes of retrieved genes
compute the true positive rate at given sizes of retrieved genes
Iterative penalized outlier detection algorithm
compute the iterative penalized outlier detection given the noise stan...
latent effect adjustment after primary projection
latent effect adjustment after primary projection
Calculate statistics and p-values
Outlier detection with a ridge penalty
plot ROC curve
These functions take a gene expression value matrix, a primary covariate vector, an additional known covariates matrix. A two stage analysis is applied to counter the effects of latent variables on the rankings of hypotheses. The estimation and adjustment of latent effects are proposed by Sun, Zhang and Owen (2011). "leapp" is developed in the context of microarray experiments, but may be used as a general tool for high throughput data sets where dependence may be involved.