Description Usage Arguments Value Note References Examples

Performs variance and mean test using qpipf on the whole pathway.

1 2 |

`expr` |
an expression matrix or ExpressionSet with colnames for samples and rownames for expression features. |

`classes` |
vector of 1,2 indicating the classes of the samples (columns). |

`graph` |
a |

`nperm` |
number of permutations. Default = 100. |

`alphaV` |
pvalue significance threshold for variance test to be used during mean test. Default = 0.05. |

`b` |
number of permutations for mean analysis. Default = 100. |

`permute` |
always performs permutations in the concentration matrix test. If FALSE, the test is made using the asymptotic distribution of the log-likelihood ratio. This option should be use only if samples size is >=40 per class. |

`paired` |
perform the test for paired sample. It assumes that class labels are ordered so that the first occurrence of class 2 is paired with the first occurrence of class 1 and so on. |

`alwaysShrink` |
always perform the shrinkage estimates of variance. |

a list with alphaVar (pvalue for the variance test) and alphaMean (pvalue for mean test).

This function is based on the Gaussian Graphical Models and to use it
in a proper way it is necessary that the graph is an Direct Acyclic
Graph. Please check any graph in input using `isAcyclic`

from ggm package.

Martini P, Sales G, Massa MS, Chiogna M, Romualdi C. Along signal paths: an empirical gene set approach exploiting pathway topology. NAR. 2012 Sep.

Massa MS, Chiogna M, Romualdi C. Gene set analysis exploiting the topology of a pathway. BMC System Biol. 2010 Sep 1;4:121.

1 2 3 4 5 6 7 8 9 10 11 | ```
if (require(graphite) & require(ALL)){
kegg <- pathways("hsapiens", "kegg")
graph <- pathwayGraph(convertIdentifiers(kegg$'Chronic myeloid leukemia', "entrez"))
genes <- nodes(graph)
data(ALL)
all <- ALL[1:length(genes),1:24]
classes <- c(rep(1,12), rep(2,12))
featureNames(all@assayData)<- genes
graph <- subGraph(genes, graph)
pathQ(all, classes, graph, nperm=100, permute=FALSE)
}
``` |

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