quickDMap: quickDMap

In TimiRGeN: Time sensitive microRNA-mRNA integration, analysis and network generation tool

Description

Creates a companion heatmap for the dendrogram made by quickDendro.

Usage

quickDMap(filt_df, miRNA_exp, mRNA_exp, distmeth, hclustmeth,
pathwayname)

Arguments

filt_df	Dataframe from the matrixFilter function.
miRNA_exp	miRNA data from using the diffExpressRes function on miRNA data.
mRNA_exp	mRNA data from using the diffExpressRes function on miRNA data.
distmeth	Dist method for hierarchical clustering. Default is "maximum".
hclustmeth	Hclust method for hierarchical clustering. Default is "ward.D".
pathwayname	Character which is the name of pathway of interest. Default is "Pathway".

Value

A heatmap with time points as the x axis and genes as the y axis. Gene order will be the same as quickDendro.

Examples

library(org.Mm.eg.db)
miR <- mm_miR[1:100,]
mRNA <- mm_mRNA[1:200,]

MAE <- startObject(miR = miR, mRNA = mRNA)

MAE <- getIdsMir(MAE, assay(MAE, 1), orgDB = org.Mm.eg.db, 'mmu')
MAE <- getIdsMrna(MAE, assay(MAE, 2), "useast", 'mmusculus')

MAE <- diffExpressRes(MAE, df = assay(MAE, 1), dataType = 'Log2FC',
                     genes_ID = assay(MAE, 3),
                      idColumn = 'GENENAME',
                      name = "miRNA_log2fc")

MAE <- diffExpressRes(MAE, df = assay(MAE, 2), dataType = 'Log2FC',
                     genes_ID = assay(MAE, 7),
                     idColumn = 'GENENAME',
                     name = "mRNA_log2fc")

Filt_df <- data.frame(row.names = c("mmu-miR-145a-3p:Adamts15",
                                   "mmu-miR-146a-5p:Acy1"),
                     corr = c(-0.9191653, 0.7826041),
                     miR = c("mmu-miR-145a-3p", "mmu-miR-146a-5p"),
                     mRNA = c("Adamts15", "Acy1"),
                     miR_Entrez = c(387163, NA),
                     mRNA_Entrez = c(235130, 109652),
                     TargetScan = c(1, 0),
                     miRDB = c(0, 0),
                     Predicted_Interactions = c(1, 0),
                     miRTarBase = c(0, 1),
                     Pred_Fun = c(1, 1))

MAE <- matrixFilter(MAE, miningMatrix = Filt_df, negativeOnly = FALSE,
                   threshold = 1, predictedOnly = FALSE)

quickDendro(filt_df=MAE[[11]], miRNA_exp=MAE[[9]],
            mRNA_exp=MAE[[10]], pathwayname = "Test")

quickDMap(filt_df=MAE[[11]], miRNA_exp=MAE[[9]],
          mRNA_exp=MAE[[10]], pathwayname = "Test")

TimiRGeN documentation built on April 17, 2021, 6:03 p.m.