neighborNet {NeighborNet} | R Documentation

## Neighbor Net: An approach to infer putative disease-specific mechanisms using neighboring gene networks.

### Description

Neighbor Net: An approach to infer putative disease-specific mechanisms using neighboring gene networks.

### Usage

    neighborNet(de, ref, listofgenes, threshold = 0.1, minsize = 2)

### Arguments

`de` | a vector including the differentially expressed genes; `de` must use the same id's as `ref` and the genes in the `listofgenes`
`ref` | the reference vector for all genes in the analysis
`listofgenes` | a list representing the neighbor networks associated to each gene; the name of the list must be the same as genes in the `de`
`threshold` | a threshold of choosing significant neighbor networks (default is 0.1)
`minsize` | minimum size of the neighbor networks that should be considered in the analysis (default is 2)

### Details

See details in the cited articles.

### Value

An object of class `graphNEL`.

### Author(s)

Sahar Ansari and Sorin Draghici

### References

Sahar Ansari, Michele Donato, Nafiseh Saberian, Sorin Draghici; An approach to infer putative disease-specific mechanisms using neighboring gene networks, Bioinformatics, Volume 33, Issue 13, 1 July 2017, Pages 1987–1994

### Examples

    # load multiple colorectal cancer study (public data available in GEO
    # ID: GSE4183, GSE9348, GSE21510, GSE32323, GSEl8671)
    # These files contains the tables, produced by the limma package with
    # added gene information.
    # The table contains the expression fold change and signficance of each
    # probe set comparing colorectal cancer disease and normal.
    load(system.file("extdata/dataColorectal4183.RData", package = "NeighborNet"))
    load(system.file("extdata/dataColorectal9348.RData", package = "NeighborNet"))
    load(system.file("extdata/dataColorectal21510.RData", package = "NeighborNet"))
    load(system.file("extdata/dataColorectal32323.RData", package = "NeighborNet"))
    load(system.file("extdata/dataColorectal8671.RData", package = "NeighborNet"))
    head(dataColorectal4183)

    load(system.file("extdata/listofgenes.RData", package = "NeighborNet"))
    head(listofgenes)

    # select differentially expressed genes for each data set at p-value below 1%
    # and absolute value for more than 1.5 and save their entrez ID in a vector de1 to de5
    pvThreshold <- 0.01
    foldThreshold <- 1.5
    de1 <- dataColorectal4183$EntrezID [
      dataColorectal4183$adj.P.Val < pvThreshold &
      abs(dataColorectal4183$logFC) > foldThreshold]
    de2 <- dataColorectal9348$EntrezID [
      dataColorectal9348$adj.P.Val < pvThreshold &
      abs(dataColorectal9348$logFC) > foldThreshold]
    de3 <- dataColorectal21510$EntrezID [
      dataColorectal21510$adj.P.Val < pvThreshold &
      abs(dataColorectal21510$logFC) > foldThreshold]
    de4 <- dataColorectal32323$EntrezID [
      dataColorectal32323$adj.P.Val < pvThreshold &
      abs(dataColorectal32323$logFC) > foldThreshold]
    de5 <- dataColorectal8671$EntrezID [
      dataColorectal8671$adj.P.Val < pvThreshold &
      abs(dataColorectal8671$logFC) > foldThreshold]
    all <- unique( c(dataColorectal4183$EntrezID, dataColorectal9348$EntrezID,
      dataColorectal21510$EntrezID, dataColorectal32323$EntrezID,
      dataColorectal8671$EntrezID))
    de <- unique( c(de1,de2,de3,de4,de5))

    sig_net <- neighborNet (de, all, listofgenes)

[Package NeighborNet version 1.6.0 Index]