isoNetwork {isomiRs} | R Documentation

## Clustering miRNAs-genes pairs in similar pattern expression

### Description

Clustering miRNAs-genes pairs

### Usage

    isoNetwork(
      mirna_rse,
      gene_rse,
      summarize = NULL,
      target = NULL,
      org = NULL,
      enrich = NULL,
      genename = "ENSEMBL",
      min_cor = -0.6,
      min_fc = 0.5
    )

### Arguments

`mirna_rse` | `SummarizedExperiment` with miRNA information. See details.
`gene_rse` | `SummarizedExperiment` with gene information. See details.
`summarize` | Character column name in `colData(rse)` to use to group samples and compare betweem miRNA/gene expression.
`target` | Matrix with miRNAs (columns) and genes (rows) target prediction (1 if it is a target, 0 if not).
`org` | `AnnotationDb` obejct. For example:(org.Mm.eg.db)
`enrich` | The output of clusterProfiler of similar functions.
`genename` | Character keytype of the gene names in gene_rse object.
`min_cor` | Numeric cutoff to consider a miRNA to regulate a target.
`min_fc` | Numeric cutoff to consider as the minimum log2FoldChange between groups to be considered in the analysis.

### Details

This function will correlate miRNA and gene expression data using a specific metadata variable to group samples and detect pattern of expression that will be annotated with GO terms. mirna_rse and gene_rse can be created using the following code:

`mi_rse = SummarizedExperiment(assays=SimpleList(norm=mirna_matrix), colData, metadata=list(sign=mirna_keep))`

where, `mirna_matrix` is the normalized counts expression, `colData` is the metadata information and `mirna_keep` the list of miRNAs to be used by this function.

### Value

list with network information

### Examples

    # library(org.Mm.eg.db)
    # library(clusterProfiler)
    data(isoExample)
    # ego <- enrichGO(row.names(assay(gene_ex_rse, "norm")),
    #                 org.Mm.eg.db, "ENSEMBL", ont = "BP")
    data <- isoNetwork(mirna_ex_rse, gene_ex_rse,
                       summarize = "group", target = ma_ex,
                       enrich = ego)
    isoPlotNet(data, minGenes = 5)

[Package isomiRs version 1.22.1 Index]