runAllMirnaModels {mirTarRnaSeq} | R Documentation

## runAllMirnaModels runModel for all miRNAs

### Description

This function runs the "runModel" function for all miRNAs and mRNA combinations of two and returns a list with significant genes and FDR models

### Usage

    runAllMirnaModels(
      mirnas,
      DiffExpmRNA,
      DiffExpmiRNA,
      miranda_data,
      prob = 0.75,
      fdr_cutoff = 0.1,
      method = "fdr",
      cutoff = 0.05,
      all_coeff = FALSE,
      mode = NULL,
      family = glm_poisson(),
      scale = 1
    )

### Arguments

`mirnas` | vector of unique miRNAs under investigation.
`DiffExpmRNA` | deferentially/expressed mRNAs expression file.
`DiffExpmiRNA` | deferentially/expressed miRNAs expression file.
`miranda_data` | getInputSpecies output file ( use low filters).
`prob` | user defined ratio for miRanda distribution for miRanda score selection default is 0.75.
`fdr_cutoff` | cutoff for FDR selection default is 0.1.
`method` | finInterResult miRNA and mRNA interrelation in two time points results in a dataframe.
`cutoff` | P-value cutoff of the model.
`all_coeff` | if true only models with all negative coefficients will be selected if false at least one negative coefficient should be in the model; default is TRUE.
`mode` | model mode, default is Null, can be changed to "multi" and "inter".
`family` | Default is glm_poisson(), for zero inflated negative binomial NB option use glm_zeroinfl(dist="negbin").
`scale` | if normalized data (FPKM,RPKM,TPM,CPM), scale to 10 etc., however the higher you go on #scale the less accuracy your p-value estimate will be.

### Value

List of run models

### Examples

    mirnas <- c("ebv-mir-bart9-5p", "ebv-mir-bart6-3p")
    x <- runAllMirnaModels(mirnas, mRNA, miRNA, miRanda,
        prob = 0.90, fdr_cutoff = 0.1, method = "fdr",
        all_coeff = TRUE, mode = "multi",
        family = glm_poisson(), scale = 100
    )

[Package mirTarRnaSeq version 1.0.0 Index]