impute.MinDet

expression matrix with MVs (either peptides or proteins)

dataSet.mvs

the q quantile used to estimate the minimum

this function performs missing values imputation by the minimum value observed

A collection of functions for left-censored missing data imputation. Left-censoring is a special case of missing not at random (MNAR)  mechanism that generates non-responses in proteomics experiments. The package also contains functions to artificially generate peptide/protein expression data (log-transformed) as random draws from a multivariate Gaussian distribution as well as a function to generate missing data (both randomly and non-randomly). For comparison reasons, the package also contains several wrapper functions for the imputation of non-responses that are missing at random. * New functionality has been added: a hybrid method that allows the imputation of missing values in a more complex scenario where the missing data are both MAR and MNAR.

Samuel Wieczorek

impute.MinDet: Imputation with min value

Description

Usage

Arguments

Value