Validate input data for estimate.subtypes()

Check whether methy.data contains all CpGs required by subtype.model.pamr or subtype.model.rf for assigning patients to four prostate cancer DNA methylation subtypes.

Usage

validate.subtype.model.cpgs(methy.data, prop.missing.cutoff = 0.3)

Arguments

methy.data

A data.frame with patients as rows (rownames give patient ids) and column names give CpG ids.

prop.missing.cutoff

The maximum proportion of missing values allowed for each required CpG.

Value

• val.passed a logical indicating whether the data passed validation

• check$required.cpgs a vector of CpG ids that are required for predicting the subtypes

• missing.cpgs a vector of CpG ids that are required but completely missing in the data

• required.cpgs.with.high.missing a vector of CpG ids that are required and have a proportion of missing values greater than prop.missing.cutoff

Examples

data('example.data');
check <- validate.subtype.model.cpgs(example.data);
stopifnot(check$val.passed);

# CpGs required to fit each model:
#check$required.cpgs;

# CpGs that are required but completely missing in your data:
#check$missing.cpgs;

# CpGs that are required and have a proportion of missing values greater than `prop.missing.cutoff`
#check$required.cpgs.with.high.missing;