priming_graph {ceRNAnetsim} | R Documentation

## Converts the given dataframe using first variable as competing and the second as miRNA. The function converts the given dataframe using first variable as competing and the second as miRNA. If user defines interaction factors as affinity or degradation, the factors are taken into account.

### Description

Converts the given dataframe using first variable as competing and the second as miRNA. The function converts the given dataframe using first variable as competing and the second as miRNA. If user defines interaction factors as affinity or degradation, the factors are taken into account.

### Usage

    priming_graph(
      df,
      competing_count,
      miRNA_count,
      aff_factor = dummy,
      deg_factor = dummy
    )

### Arguments

`df` | A data frame that includes the miRNA and competing targets.
`competing_count` | The counts (or expression) of competing elements of the dataset.
`miRNA_count` | The counts (or expression) of repressive element (miRNA) of the dataset.
`aff_factor` | The parameter/s of binding between miRNA and targets.
`deg_factor` | The parameter/s for degradation of bound miRNA:target complex.

### Details

priming_graph provides grouping of competing targets and evaluation of targets within the groups taking into account miRNA:target, target:total target, interaction and degradation parameters. The target groups are determined according to miRNAs. If the factors that are important in target interactions are specified as arguments, the factors also are evaluated separately within each group. priming_graph also calculates the miRNA efficiency in steady-state conditions. It is assumed that quantity of competing targets and miRNAs are shown in the steady-state system after the miRNAs exhibit repressive efficiency. Note that the data must not include missing values such as NA or '-'.

### Value

the graph object.

### Examples

    data('minsamp')

    priming_graph(minsamp, Competing_expression, miRNA_expression)

    priming_graph(minsamp, Competing_expression, miRNA_expression,
        aff_factor = c(seed_type,energy), deg_factor = region)

[Package ceRNAnetsim version 1.0.0 Index]