multiReg: multiReg

View source: R/multiReg.R

multiRegR Documentation

multiReg

Description

Creates a new matrix containing the gene of interest and each binding partner that it interacts with.

Usage

multiReg(MAE, gene_interest, mRNAreg, filt_df, miRNA_exp, mRNA_exp)

Arguments

MAE

Input MAE which stores results from multiReg It is recommended to use the MAE which was used in matrixFilter.

gene_interest

Name of gene of interest. Full string required with no spelling mistakes e.g. "mmu-miR-140-5p", "Ffg1", "hsa-miR-29a-5p". If gene of interest is an mRNA, mRNAreg must be TRUE. Otherwise, if the gene of interest is a miRNA, then mRNAreg must be FALSE.

mRNAreg

TRUE or FALSE. Is the gene of interest a mRNA? Default is TRUE.

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

Value

A matrix which contains the gene of interest and all binding partners. Their values (Log2FC or ave exp) for each time point are also produced.

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)

MAE <- multiReg(MAE = MAE, gene_interest = "Adamts15",
                mRNAreg =TRUE, filt_df=MAE[[11]], miRNA_exp=MAE[[9]],
                mRNA_exp=MAE[[10]])

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