Minimum Probability Imputation

Impute missing values using random draws from the left-censored gaussian distribution. Missing values are imputed on the log2 intensity scale and then transformed back to the original scale.

Usage

impute_min_prob(x, by = NULL, q = 0.01, tune.sigma = 1, ...)

# S3 method for class 'glyexp_experiment'
impute_min_prob(x, by = NULL, q = 0.01, tune.sigma = 1, ...)

# S3 method for class 'matrix'
impute_min_prob(x, by = NULL, q = 0.01, tune.sigma = 1, ...)

# Default S3 method
impute_min_prob(x, by = NULL, q = 0.01, tune.sigma = 1, ...)

Arguments

x

Either a glyexp_experiment object or a matrix. If a matrix, rows should be variables and columns should be samples.

by

Either a column name in sample_info (string) or a factor/vector specifying group assignments for each sample. Used for grouping when imputing missing values.

q

Quantile used to estimate the lower-intensity center for each sample. Default is 0.01.

tune.sigma

Non-negative multiplier for the standard deviation of the left-censored draw distribution. Default is 1.

...

Reserved for backward compatibility. Extra arguments are not supported.

Value

Returns the same type as the input. If x is a glyexp_experiment, returns a glyexp_experiment with missing values imputed. If x is a matrix, returns a matrix with missing values imputed.