quickPathwayTC: quickPathwayTC

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

Description

Plots time series data from the pathway of interest. Genes which pass a user defined threshold will be highlighted.

Usage

quickPathwayTC(filt_df, miRNA_exp, mRNA_exp, morethan, threshold,
 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.
morethan	TRUE or FALSE. Default is TRUE.
threshold	Integer that is user defined. Default is 1.
pathwayname	Character which is the name of pathway of interest. Default is "Pathway".

Value

Line plot of all the genes of interest from a pathway of interest.

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)

quickPathwayTC(filt_df=MAE[[11]], miRNA_exp=MAE[[9]],
               mRNA_exp=MAE[[10]], morethan = TRUE, threshold =1,
               pathwayname = "Test")

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