The package contains 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.
|Date of publication||2015-01-19 07:09:10|
|Maintainer||Cosmin Lazar <firstname.lastname@example.org>|
|License||GPL (>= 2)|
generate.ExpressionData: Generate Peptide/Protein Expression Data
generate.RollUpMap: Generates peptide to protein map.
impute.MAR: Generic function for the imputation of MAR/MCAR missing data
impute.MAR.MNAR: Hybrid imputation method
impute.MinDet: Imputation of left-censored missing data using a...
impute.MinProb: Imputation of left-censored missing data using stochastic...
impute.QRILC: Imputation of left-censored missing data using QRILC method.
impute.wrapper.KNN: Wrapper function for KNN imputation.
impute.wrapper.MLE: MLE-based imputation of missing data.
impute.wrapper.SVD: SVD-based imputation.
impute.ZERO: Imputation of missing entries by '0'.
insertMVs: Generates missing data in a complete data matrix.
intensity_PXD000022: Dataset PXD000022 from ProteomeXchange.
intensity_PXD000052: Dataset PXD000052 from ProteomeXchange.
intensity_PXD000438: Dataset PXD000438 from ProteomeXchange.
intensity_PXD000501: Dataset PXD000501 from ProteomeXchange.
model.Selector: Model selector for hybrid missing data imputation
pep2prot: Peptide to protein mapping.