annotatePC {GenomicSuperSignature} | R Documentation

## Annotate top PCs from the dataset

### Description

This function finds the RAV scored highest with the top PCs of the dataset, including RAVs with the negative average silhouette.

### Usage

    annotatePC(
      PCnum,
      val_all,
      RAVmodel,
      n = 5,
      scoreCutoff = 0.5,
      nesCutoff = NULL,
      simplify = TRUE,
      abs = FALSE,
      trimed_pathway_len = 45
    )

### Arguments

`PCnum` | A numeric vector. PC number of your dataset that you want to get the annotation results. The vector can contain any integer number among `1:8`.
`val_all` | The output from `validate`
`RAVmodel` | The RAVmodel used to generate the input for the argument, `val_all`.
`n` | An integer. Default is 5. The number of the top enriched pathways to print out. If there are fewer than n pathways passed the cutoff, it will print out `NA`.
`scoreCutoff` | A numeric value for the minimum correlation. Default is 0.5.
`nesCutoff` | A numeric value for the minimum NES. Default is `NULL` and the suggested value is 3.
`simplify` | A logical. Under default (`TRUE`), the output will be a data frame with the number of column same as the length of `PCnum` argument, and the number of row same as the `n` argument. If it is set to `FALSE`, the output will be a list with the length of `PCnum` argument, where each element is a data frame containing detailed GSEA output of enriched pathways.
`abs` | Default is `FALSE`. If it's set to `TRUE`, the enriched pathways will be listed based on `abs(NES)`.
`trimed_pathway_len` | Positive inter values, which is the display width of pathway names. Default is 45.

### Value

A data frame of a list based on the `simplify` argument. Check the output detail above.

### Examples

    data(miniRAVmodel)
    library(bcellViper)
    data(bcellViper)
    val_all <- validate(dset, miniRAVmodel)
    annotatePC(2, val_all, miniRAVmodel)

[Package GenomicSuperSignature version 1.0.1 Index]