Package: imputeLCMD 2.1
imputeLCMD: A Collection of Methods for Left-Censored Missing Data Imputation
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.
Authors:
imputeLCMD_2.1.tar.gz
imputeLCMD_2.1.zip(r-4.5)imputeLCMD_2.1.zip(r-4.4)imputeLCMD_2.1.zip(r-4.3)
imputeLCMD_2.1.tgz(r-4.4-any)imputeLCMD_2.1.tgz(r-4.3-any)
imputeLCMD_2.1.tar.gz(r-4.5-noble)imputeLCMD_2.1.tar.gz(r-4.4-noble)
imputeLCMD_2.1.tgz(r-4.4-emscripten)imputeLCMD_2.1.tgz(r-4.3-emscripten)
imputeLCMD.pdf |imputeLCMD.html✨
imputeLCMD/json (API)
| # Install 'imputeLCMD' in R: |
| install.packages('imputeLCMD', repos = c('https://samwieczorek.r-universe.dev', 'https://cloud.r-project.org')) |
- intensity_PXD000022 - Dataset PXD000022 from ProteomeXchange.
- intensity_PXD000052 - Dataset PXD000052 from ProteomeXchange.
- intensity_PXD000438 - Dataset PXD000438 from ProteomeXchange.
- intensity_PXD000501 - Dataset PXD000501 from ProteomeXchange.
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:23debc0c09. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 15 2024 |
| R-4.5-win | OK | Nov 15 2024 |
| R-4.5-linux | OK | Nov 15 2024 |
| R-4.4-win | OK | Nov 15 2024 |
| R-4.4-mac | OK | Nov 15 2024 |
| R-4.3-win | OK | Nov 15 2024 |
| R-4.3-mac | OK | Nov 15 2024 |
Exports:generate.ExpressionDatagenerate.RollUpMapimpute.MARimpute.MAR.MNARimpute.MinDetimpute.MinProbimpute.QRILCimpute.wrapper.KNNimpute.wrapper.MLEimpute.wrapper.SVDimpute.ZEROinsertMVsmodel.Selectorpep2prot
Dependencies:BiobaseBiocGenericsgenericsgmmimputelatticeMASSMatrixmvtnormnormpcaMethodsRcppsandwichtmvtnormzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate expression data | generate.ExpressionData |
| Generate roll up map | generate.RollUpMap |
| imputation under MAR/MCAR hypothesis | impute.MAR |
| Imputation under MCAR and MNAR hypothesis | impute.MAR.MNAR |
| Imputation with min value | impute.MinDet |
| Imputation by random draws | impute.MinProb |
| imputation based on quantile regression | impute.QRILC |
| Imputation with KNN | impute.wrapper.KNN |
| imputation using the EM algorithm | impute.wrapper.MLE |
| imputation based on SVD algorithm | impute.wrapper.SVD |
| Imputation by 0. | impute.ZERO |
| Generates missing values in data. | insertMVs |
| Dataset PXD000022 from ProteomeXchange. | intensity_PXD000022 |
| Dataset PXD000052 from ProteomeXchange. | intensity_PXD000052 |
| Dataset PXD000438 from ProteomeXchange. | intensity_PXD000438 |
| Dataset PXD000501 from ProteomeXchange. | intensity_PXD000501 |
| Identifies row in the data matrix affected by a MNAR missingness mechanism | model.Selector |
| peptide to protein roll-up | pep2prot |
