This function summarizes the missing data in a methyl_surro object. It identifies probes with partial missing data (missing observations) and probes missing from all samples (missing probes), along with comprehensive summary statistics.
Value
A list of class methyl_miss with the following elements:
- missing_obs
A named numeric vector with the proportion of missing observations for each probe where this value is greater than 0 but less than 1.
- missing_probes
A character vector of probes that are missing in all samples.
- summary
A list containing summary statistics about the missing data patterns.
The summary component contains:
- total_probes
Total number of probes in the methylation matrix.
- total_samples
Total number of samples in the methylation matrix.
- n_complete_probes
Number of probes with no missing values.
- n_missing_obs
Number of probes with partial missing data.
- n_missing_probes
Number of completely missing probes.
- overall_missing_rate
Proportion of all matrix values that are missing.
- missing_obs_rate
Proportion of probes that have partial missing data.
- missing_probes_rate
Proportion of probes that are completely missing.
- complete_probes_rate
Proportion of probes that are complete.
Examples
# Load Methylation Beta Matrix
data(beta_matrix_miss, package = "MethylSurroGetR")
# Load Weights Data Frame and create vector
data(wts_df, package = "MethylSurroGetR")
wts_vec_lin <- setNames(wts_df$wt_lin, rownames(wts_df))
# Build the methyl_surro Object
surrogate <- surro_set(methyl = beta_matrix_miss,
weights = wts_vec_lin,
intercept = "Intercept")
#> Added 5 missing probes with NA values (50.0% of weight probes missing from methylation data).
#> Filtered methylation matrix from 15 to 10 probes to match weights.
# Summarizing Missing Values
missing_summary <- methyl_miss(methyl_surro = surrogate)
print(missing_summary)
#> Missing Data Summary for methyl_surro Object
#> ============================================
#>
#> Total probes: 10
#> Total samples: 5
#> Complete probes: 3 (30.0%)
#> Probes with missing observations: 2 (20.0%)
#> Completely missing probes: 5 (50.0%)
#> Overall missing rate: 58.0%
#>
#> Probes with partial missing data:
#> cg02 cg07
#> 0.6 0.2
#>
#> Completely missing probes:
#> cg03, cg06, cg11, cg15, cg18
# Access specific components
missing_summary$missing_obs
#> cg02 cg07
#> 0.6 0.2
missing_summary$summary$overall_missing_rate
#> [1] 0.58