mlclassCox {highMLR} | R Documentation |
Applications of machine learning in survival analysis by prognostic classification of genes by CoxPH model.
Description
Applications of machine learning in survival analysis by prognostic classification of genes by CoxPH model.
Usage
mlclassCox(m, n, idSurv, idEvent, Time, s_ID, per = 20, fold = 3, data)
Arguments
m |
Starting column number from where high dimensional variates to be selected. |
n |
Ending column number till where high dimensional variates to be selected. |
idSurv |
"Column/Variable name" consisting duration of survival. |
idEvent |
"Column/Variable name" consisting survival event. |
Time |
"Column/Variable name" consisting Times of repeated observations. |
s_ID |
"Column/Variable name" consisting unique identification for each subject. |
per |
Percentage value for ordering, default=20. |
fold |
Number of folds for re-sampling, default=3. |
data |
High dimensional data containing survival observations with multiple covariates. |
Value
A list of genes as per their classifications
- GeneClassification
List of genes classified using Cox proportional hazard model
- GeneClassification$Positive_Gene
Sublist of genes classified as positive genes
- GeneClassification$Negative_Gene
Sublist of genes classified as negative genes
- GeneClassification$Volatile_Gene
Sublist of genes classified as volatile genes
- Result
A dataframe consisting threshold values with corresponding coefficients and p-values.
Examples
## Not run:
data(srdata)
mlclassCox(m=50,n=59,idSurv="OS",idEvent="event",Time="Visit",s_ID="ID",per=20,fold=3,data=srdata)
## End(Not run)