linearRegr: linearRegr

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

Description

Creates a linear model between a mRNA or miRNA of choice and a selection of it's filtered binding partners. The model is based on the users design.

Usage

linearRegr(mreg, colselect, colpair, alterpairs)

Arguments

mreg	Matrix generated from the multiReg function. This should be found as an assay within the MAE used during the multiReg function.
colselect	Column from mreg which contain the gene of interest. Default is 2.
colpair	Column of binding parter of the gene of interest. Default is 3. If NANs are found, test alternative formulas.
alterpairs	Column(s) of other binding partners of the gene of interest. This can include any numer of columns. If NANs are found, test alternative formulas. e.g. = 4:7, c(4, 6, 8), 4.

Value

A linear regression model which represents miRNA-mRNA interaction(s) which can be further explored.

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]])

model1 <- linearRegr(mreg = MAE[[12]], colselect =2, colpair =3)
summary(model1$regression)

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