The methyl_miss class stores comprehensive information about missing data patterns
in a methyl_surro object. Objects of this class are created by the
methyl_miss function and provide detailed summaries of both partial and
complete missingness.
Object Structure
A methyl_miss object is a list with class "methyl_miss" containing:
missing_obsA named numeric vector showing the proportion of missing observations (0 to 1) for each probe that has partial missingness (i.e., missing in some but not all samples). Names are CpG probe IDs.
missing_probesA character vector of CpG probe IDs that are completely missing (i.e., missing in all samples).
summaryA list containing overall summary statistics (see details below).
Summary Statistics
The summary component contains:
total_probesTotal number of CpG probes in the methylation matrix.
total_samplesTotal number of samples in the methylation matrix.
n_complete_probesNumber of probes with no missing values.
n_missing_obsNumber of probes with partial missing data (some but not all samples missing).
n_missing_probesNumber of completely missing probes (all samples missing).
overall_missing_rateProportion of all matrix values that are missing (0 to 1).
missing_obs_rateProportion of probes with partial missing data (0 to 1).
missing_probes_rateProportion of probes that are completely missing (0 to 1).
complete_probes_rateProportion of probes with no missing values (0 to 1).
Creating methyl_miss Objects
Objects are created using methyl_miss:
# Create methyl_surro object
my_surro <- surro_set(beta_matrix_miss, weights_vec, "Intercept")
# Assess missing data
miss_info <- methyl_miss(my_surro)Accessing Information
Components can be accessed using standard list notation:
# View probes with partial missingness
miss_info$missing_obs
# View completely missing probes
miss_info$missing_probes
# Access summary statistics
miss_info$summary$overall_missing_rate
miss_info$summary$n_missing_probesPrint Method
The package provides a print method that displays a formatted summary:
print(miss_info)This shows an organized view of missing data patterns and summary statistics.
See also
methyl_miss for creating objects,
methyl_surro for the input object type,
reference_fill and impute_obs for addressing missing data
