Clustering miRNAs-genes pairs in similar pattern expression

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Description

Clustering miRNAs-genes pairs in similar pattern expression

Usage

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isoNetwork(mirna_rse, gene_rse, target, summarize = "group", org,
  genename = "ENSEMBL", min_cor = -0.6)

Arguments

mirna_rse

SummarizedExperiment with miRNA information. See details.

gene_rse

SummarizedExperiment with gene information. See details.

target

matrix with miRNAs (columns) and genes (rows) target prediction (1 if it is a target, 0 if not).

summarize

character column name in colData(rse) to use to group samples and compare betweem miRNA/gene expression.

org

AnnotationDb. (org.Mm.eg.db)

genename

character keytype of the gene names in gene_rse object.

min_cor

numeric cutoff to consider a miRNA to regulate a target

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.

Examples

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library(org.Mm.eg.db)
library(clusterProfiler)
data(isoExample)
ego <- enrichGO(row.names(assay(gene_ex_rse, "norm")), org.Mm.eg.db, ont = "BP", keytype="ENSEMBL")
data = isoNetwork(mirna_ex_rse, gene_ex_rse, ma_ex, org=ego@result)
isoPlotNet(data)