quickDendro: quickDendro

View source: R/quickDendro.R

quickDendroR Documentation

quickDendro

Description

Ceates a dendrogram of the genes from the pathway of interest.

Usage

quickDendro(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 dendrogram with the genes on the Y axis and the distances on the X axis.

Examples

library(org.Mm.eg.db)

miR <- mm_miR[1:50,]

mRNA <- mm_mRNA[1:100,]

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', orgDB = org.Mm.eg.db)

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")

Krutik6/TimiRGeN documentation built on Jan. 27, 2024, 7:46 p.m.