Description Usage Arguments Value Examples
This method takes a gene to gene distance matrix and computes the summed proximity of each gene to a set of genes. The set of genes is presumably a collection of known genes for a phenotype of interest.
1 2 3 |
kernel |
Required. Produced by |
pheno.gene.set |
Required. A vector of previously known phenotype-related genes. WIll automatically be coerced to uppercase unless overriden (see autocaps param). |
autocaps |
Optional. Defaults to TRUE. Converts all entries in pheno.gene.set to uppercase to ensure accurate mapping to genes in kernel. |
invert.distance |
Optional. Defaults to FALSE. If using a different kernel other than
the difussion kernel produced by |
ignore.neighbors |
Optional. Defaults to FALSE. If set to TRUE, then predictions will
only be generated for genes that do not directly interact with the pheno.gene.set. This allows
for investigation of indirect interactions that can be detected with ignition's diffusion
method. Note that if this is set to TRUE, an adjacency matrix such as that produced by
|
adj.matrix |
Optional. An adjacency matrix of the same dimensions as the kernel. If using a custom kernel, make sure that the ith row/col of the kernel correspond to the ith row/col of the adjacency matrix. If the user has specified ignore.neighbors = TRUE, then this argument is required. |
weight.vector |
Optional. User may provide a vector of confidence measures for each gene in the specified seed set. We recommend a scale from 0 to 1, with 1 being highest possible confidence that the gene is associated with the phenotype being studied. weight.vector should be same length as pheno.gene.set |
A data frame containing the computed percentiles and Z scores for each gene.
1 2 3 4 5 | data(ignition.example.edges)
adj.matrix = CreateAdjMatrix(ignition.example.edges)
kernel = CreateKernel(adj.matrix)
known.gene.set = c('B', 'I')
GeneratePredictions(kernel, known.gene.set)
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