plotRankedFeature {BioMM} | R Documentation

## Plot top outcome-associated features

### Description

Plot top ranked outcome-associated features from stage-2 data. The ranking criteria are based on metrics such as Nagelkerke pseudo R-square.

### Usage

    plotRankedFeature(data, posF = TRUE, topF = 10, blocklist,
      stratify = c("gene", "pathway", "chromosome"), rankMetric = c("cor",
      "AUC", "ACC", "R2", "size"), colorMetric = c("cor", "AUC", "ACC", "R2",
      "size"), core = MulticoreParam(), fileName = NULL)

### Arguments

`data` | The input stage-2 data (either data.frame or matrix). Rows are the samples, columns are gene IDs, or pathway names or chromosome IDs, except that the first column is the label (the outcome).
`posF` | A logical value indicating if only positively outcome-associated features should be used. (Default: TRUE)
`topF` | The top ranked number of features at stage-2 (`topF` >= 2). (Default: 10)
`blocklist` | A list of matrices with block IDs as the associated list member names. The block IDs identical to the stage-2 feature names. The block can be gene, pathway or chromosome. For each matrix, rows are the samples and columns are the probe names, except that the first column is named 'label'. See also `omics2genelist`; `omics2pathlist`; `omics2chrlist`
`stratify` | A string. The applied stratification method to generate `blocklist`. Valid options are c('gene', 'pathway', 'chromosome').
`rankMetric` | A string representing the metrics used for ranking. Valid options are c('cor', 'AUC', 'ACC', 'R2', 'size'). 'size' is the block size.
`colorMetric` | A string representing the metric used to color the plot. Valid options are c('cor', 'AUC', 'ACC', 'R2', 'size'). 'size' is the block size.
`core` | The number of cores used for computation. (Default: 10)
`fileName` | The plot file name. (Default: 'plottopF.png')

### Details

If the argument `posF` is TRUE, and no positively outcome-associated features are present in stage-2 data , then an error is reported. In addition, if `topF` is bigger than the number of positively outcome-associated features, an error is returned.

### Value

An output image file.

### References

Perlich, C., & Swirszcz, G. (2011). On cross-validation and stacking: Building seemingly predictive models on random data. ACM SIGKDD Explorations Newsletter, 12(2), 11-15.

### See Also

`omics2genelist`; `omics2pathlist`; `omics2chrlist`

[Package BioMM version 1.0.0 Index]