heat_vis {anamiR} | R Documentation |
This function would base on Fold-Change information from the output of negative_cor, differExp_discrete and show heatmaps to users. Note that if miRNA-gene interactions (row) from input are larger than 100, the lable in plot would be unclear.
heat_vis(cor_data, mrna_d, mirna_21)
cor_data |
matrix format generated from negative_cor. |
mrna_d |
differential expressed data in data.frame format, with sample name in columns and gene symbol in rows, which is generated by differExp_discrete or differExp_continuous. |
mirna_21 |
differential expressed data in data.frame format, with sample name in columns and miRNAl in rows, which is generated by differExp_discrete or differExp_continuous, miRNA should be miRBase 21 version now. |
heatmap plots of miRNA and gene.
heatmap.2
for plot.
## Use the internal dataset data("mirna", package = "anamiR", envir = environment()) data("pheno.mirna", package = "anamiR", envir = environment()) data("mrna", package = "anamiR", envir = environment()) data("pheno.mrna", package = "anamiR", envir = environment()) ## SummarizedExperiment class require(SummarizedExperiment) mirna_se <- SummarizedExperiment( assays = SimpleList(counts=mirna), colData = pheno.mirna) ## SummarizedExperiment class require(SummarizedExperiment) mrna_se <- SummarizedExperiment( assays = SimpleList(counts=mrna), colData = pheno.mrna) ## Finding differential miRNA from miRNA expression data with t.test mirna_d <- differExp_discrete( se = mirna_se, class = "ER", method = "t.test" ) ## Finding differential mRNA from mRNA expression data with t.test mrna_d <- differExp_discrete( se = mrna_se, class = "ER", method = "t.test" ) ## Convert annotation to miRBse 21 mirna_21 <- miR_converter(data = mirna_d, original_version = 17) ## Correlation cor <- negative_cor(mrna_data = mrna_d, mirna_data = mirna_21) ## Draw heatmap heat_vis(cor, mrna_d, mirna_21)