isoNetwork {isomiRs} | R Documentation |
Clustering miRNAs-genes pairs
isoNetwork( mirna_rse, gene_rse, summarize = NULL, target = NULL, org = NULL, enrich = NULL, genename = "ENSEMBL", min_cor = -0.6, min_fc = 0.5 )
mirna_rse |
|
gene_rse |
|
summarize |
Character column name in |
target |
Matrix with miRNAs (columns) and genes (rows) target prediction (1 if it is a target, 0 if not). |
org |
|
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. |
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.
list with network information
# 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)