This function creates a matrix with rows (genes) and columns (mirnas) with values indicating if miRNA-gene pair is target according putative targets and negative correlation of the expression of both molecules.

find_targets(mirna_rse, gene_rse, target, summarize = "group",
  min_cor = -0.6)

Arguments

mirna_rse

SummarizedExperiment::SummarizedExperiment with miRNA information. See details.

gene_rse

SummarizedExperiment::SummarizedExperiment with gene information. See details.

target

Matrix with miRNAs (columns) and genes (rows) target prediction values (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.

min_cor

Numeric cutoff for correlation value that will be use to consider a miRNA-gene pair as valid.

Value

mirna-gene matrix

Examples

pairs <- as.matrix(data.frame(row.names=c("gene1", "gene2"), mirna1=c(0,1), mirna2=c(1,0))) mirna_matrix <- as.matrix(data.frame(row.names=c("mirna1", "mirna2"), time0_1=c(1,1),time0_2=c(1.2,0.9), time1_1=c(8,8),time1_2=c(8.2,7.9))) gene_matrix <- as.matrix(data.frame(row.names=c("gene1", "gene2"), time0_1=c(8,8),time0_2=c(8.2,7.9), time1_1=c(1,1),time1_2=c(1.2,0.9))) mirna_col <- data.frame(row.names=c("time0_1","time0_2","time1_1","time1_2"), group=c("t0","t0","t1","t1")) gene_col <- data.frame(row.names=c("time0_1","time0_2","time1_1","time1_2"), group=c("t0","t0","t1","t1")) mirna <- SummarizedExperiment(assays=SimpleList(norm=as.matrix(mirna_matrix)), colData= mirna_col) gene <- SummarizedExperiment(assays=SimpleList(norm=as.matrix(gene_matrix)), colData= gene_col) find_targets(mirna, gene, pairs)
#> Number of mirnas 2
#> Number of genes 2
#> Factors genest0t1
#> Factors mirnast0t1
#> Order genest0t0t1t1
#> Order mirnast0t0t1t1
#> Calculating cor matrix
#> Dimmension of cor matrix: 2 2
#> mirna1 mirna2 #> gene1 0 -1 #> gene2 -1 0