quickTCPred {TimiRGeN} | R Documentation

## quickTCPred

### Description

Creates a regression plot over the time course, which compares data and a simulation which was predicted using the data. Data is based on the model formula used in the multiReg function and linearRegr function. R.squared and p value are also calculated and pasted into the plot.

### Usage

    quickTCPred(model, reg_df)

### Arguments

`model` | Linear model which was generated by the linearRegr function.
`reg_df` | Matrix/assay which which was generated by the multiReg function. Should be in the MAE used during the multiReg function.

### Value

A linear regression plot with data and a simulation.

### 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)

    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)

    quickTCPred(model = model1, reg_df = MAE[[12]])

[Package TimiRGeN version 1.2.0 Index]