imp4p (version 1.2)

Imputation for Proteomics

Description

Functions to analyse missing value mechanisms and to impute data sets in the context of bottom-up MS-based proteomics.

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Version

Install

install.packages('imp4p')

Monthly Downloads

251

Version

1.2

License

GPL-3

Maintainer

Quentin Giai Gianetto

Last Published

September 2nd, 2021

Functions in imp4p (1.2)

estim.mix

Estimation of a mixture model of MCAR and MNAR values in each column of a data matrix.

impute.mle

Imputing missing values using a maximum likelihood estimation (MLE).

impute.mi

Imputation of data sets containing peptide intensities with a multiple imputation strategy.

impute.RF

Imputing missing values using Random Forest.

mi.mix

Multiple imputation from a matrix of probabilities of being MCAR for each missing value.

impute.mix

Imputation using a decision rule under an assumption of a mixture of MCAR and MNAR values.

impute.rand

Imputation of peptides with a random value.

miss.mcar.process

Estimating the MCAR mechanism in a sample.

impute.pa

Imputation of peptides having no value in a biological condition (present in a condition / absent in another).

pi.mcar.logit

Estimating the proportion of MCAR values in a sample using a logit model.

impute.igcda

Imputing missing values by assuming that the distribution of complete values is Gaussian in each column of an input matrix. This algorithm is named "Imputation under a Gaussian Complete Data Assumption" (IGCDA).

impute.slsa

Imputing missing values using an adaptation of the LSimpute algorithm (Bo et al. (2004)) to experimental designs. This algorithm is named "Structured Least Squares Algorithm" (SLSA).

pi.mcar.probit

Estimating the proportion of MCAR values in a sample using a probit model.

miss.total.process

Estimating the missing data mechanism in a sample.

pi.mcar.karpievitch

Estimating the proportion of MCAR values in biological conditions using the method of Karpievitch (2009).

prob.mcar.tab

Estimation of a matrix of probabilities that missing values are MCAR.

prob.mcar

Estimation of a vector of probabilities that missing values are MCAR.

sim.data

Simulation of data sets by controlling the proportion of MCAR values and the distribution of MNAR values.

translatedRandomBeta

Function to generated values following a translated Beta distribution

gen.cond

Function allowing to create a vector indicating the membership of each sample to a condition.

imp4p-package

Introduction to the IMP4P package

estim.bound

Estimation of lower and upper bounds for missing values.

fast_apply_nb_not_na

Function similar to the function apply(X,dim,function(x)sum(!is.na(x))).

fast_apply_nb_na

Function similar to the function apply(X,dim,function(x)sum(is.na(x))).

impute.PCA

Imputing missing values using Principal Components Analysis.

fast_sim

Function to compute similarity measures between a vector and each row of a matrix.

fast_apply_sum_na_rm_T

Function similar to the function apply(X,dim,sum,na.rm=TRUE).

fast_apply_sd_na_rm_T

Function similar to the function apply(X,dim,sd,na.rm=TRUE).