plotRankedFeature {BioMM} | R Documentation |
Plot top ranked outcome-associated features from stage-2 data. The ranking criteria are based on metrics such as Nagelkerke pseudo R-square.
plotRankedFeature(data, posF = TRUE, topF = 10, blocklist, rankMetric = c("AUC", "ACC", "R2", "size"), colorMetric = c("AUC", "ACC", "R2", "size"), core = MulticoreParam(), fileName = NULL)
data |
The input stage-2 data (either data.frame or matrix). Rows are the samples, columns are pathway names, 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 ( |
blocklist |
A list of matrices with block IDs as the associated list
member names. The block IDs identical to the stage-2 feature names.
For each matrix, rows are the samples and columns are the probe names,
except that the first column is named 'label'. See also
|
rankMetric |
A string representing the metrics used for ranking. Valid options are c('AUC', 'ACC', 'R2', 'size'). 'size' is the block size. |
colorMetric |
A string representing the metric used to color the plot. Valid options are c('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') |
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.
An output image file and the summary statistics of the top pathways.
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.