isoNetwork: Clustering miRNAs-genes pairs in similar pattern expression

In isomiRs: Analyze isomiRs and miRNAs from small RNA-seq

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)

isomiRs documentation built on Jan. 31, 2021, 2 a.m.