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.
findTargets(mirna_rse, gene_rse, target, summarize = "group", min_cor = -0.6)
mirna_rse | SummarizedExperiment::SummarizedExperiment with miRNA information. See details. |
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gene_rse | SummarizedExperiment::SummarizedExperiment with gene information. See details. |
target | Data.frame with two columns: gene and miRNA. |
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. |
mirna-gene matrix
data(isoExample) mirna_ma <- matrix(rbinom(20*25, c(0, 1), 1), ncol = 20) colnames(mirna_ma) <- rownames(mirna_ex_rse) rownames(mirna_ma) <- rownames(gene_ex_rse) corMat <- findTargets(mirna_ex_rse, gene_ex_rse, mirna_ma)#> Error in pairsMatrix(target): Need a data.frame with 2 columns: gene, mir.