View source: R/hierarchicalFDR.R

selFDR | R Documentation |

Select groups from hierarchical testing procedure with FDR control (hierarchicalFDR)

selFDR(out, alpha = 0.05, global = TRUE, outer = TRUE)

`out` |
output of hierarchicalFDR function |

`alpha` |
control level for test |

`global` |
if FALSE the provided alpha is the desired level control for each family. |

`outer` |
if TRUE, the FDR is controlled only on outer node (rejected groups without rejected children). If FALSE, it is controlled on the full tree. |

See the reference for mode details about the method.

If each family is controlled at a level alpha, we have the following control: FDR control of full tree: alpha * delta * 2 (delta = 1.44) FDR control of outer node: alpha * L * delta * 2 (delta = 1.44)

a list containing:

- toSel
vector of boolean. TRUE if the group is selected

- groupId
Names of groups

- local.alpha
control level for each family of hypothesis

- global.alpha
control level for the tree (full tree or outer node)

Yekutieli, Daniel. "Hierarchical False Discovery Rate-Controlling Methodology." Journal of the American Statistical Association 103.481 (2008): 309-16.

hierarchicalFDR

set.seed(42) X <- simuBlockGaussian(50, 12, 5, 0.7) y <- X[, c(2, 7, 12)] %*% c(2, 2, -2) + rnorm(50, 0, 0.5) res <- MLGL(X, y) test <- hierarchicalFDR(X, y, res$group[[20]], res$var[[20]]) sel <- selFDR(test, alpha = 0.05)

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.