findOnepwaySynexprs {attract} | R Documentation

## Internal function - finds the synexpression groups for a single given pathway.

### Description

Internal function - finds the synexpression groups for a single given pathway.

### Usage

    findOnepwaySynexprs(myIDs, myDataSet, cellTypeTag, min.clustersize = 5, removeGenes = NULL, ...)

### Arguments

`myIDs` | a single character string denoting the KEGG or reactome ID of the pathway module to be analyzed or a character codevector of gene names of a pathway.
`myDataSet` | `AttractorModuleSet` object, output of the `findAttractors` step. This could also be an `ExpressionSet` object.
`cellTypeTag` | character string of the variable name which stores the cell-lineages or experimental groups of interest for the samples in the data set (this string should be one of the column names of pData(myEset)).
`min.clustersize` | integer specifying the minimum number of genes that must be present in clusters that are inferred.
`removeGenes` | `vector` of probes that specify those genes who demonstrate little variability across the different celltypes and thus should be removed from downstream analysis.
`...` | additional arguments.

### Details

This function is called internally by `calcFuncSynexprs`. Users should use `calcFuncSynexprs` rather than calling `findOnepwaySynexprs` directly.

### Value

A `SynExpressionSet` object is returned.

### Author(s)

Jessica Mar

### Examples

    ## Not run:
    data(subset.loring.eset)
    attractor.states <- findAttractors(subset.loring.eset, "celltype", nperm=10, annotation="illuminaHumanv1.db")
    remove.these.genes <- removeFlatGenes(subset.loring.eset, "celltype", contrasts=NULL, limma.cutoff=0.05)
    map.syn <- findOnepwaySynexprs("04010", attractor.states, "celltype", removeGenes=remove.these.genes)
    vec.geneid <- c("GI_17999531-S","GI_17978503-A")
    custom.syn <- findSynexprs(vec.geneid, subset.loring.eset, "celltype", removeGenes=remove.these.genes)

    ## End(Not run)

[Package attract version 1.44.0 Index]