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Two-Step Lasso (TS-Lasso) and compound minimum methods to recover the abundance of missing peaks in mass spectrum analysis. TS-Lasso is an imputation method that handles various types of missing peaks simultaneously. This package provides the procedure to generate missing peaks (or data) for simulation study, as well as a tool to estimate and visualize the proportion of missing at random.
| Version: | 0.0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | utils, glmnet, ggplot2, reshape2 |
| Published: | 2019-01-11 |
| DOI: | 10.32614/CRAN.package.GMSimpute |
| Author: | Qian Li [aut, cre] |
| Maintainer: | Qian Li <qian.li10000 at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | GMSimpute results |
| Reference manual: | GMSimpute.pdf |
| Package source: | GMSimpute_0.0.1.0.tar.gz |
| Windows binaries: | r-devel: GMSimpute_0.0.1.0.zip, r-release: GMSimpute_0.0.1.0.zip, r-oldrel: GMSimpute_0.0.1.0.zip |
| macOS binaries: | r-release (arm64): GMSimpute_0.0.1.0.tgz, r-oldrel (arm64): GMSimpute_0.0.1.0.tgz, r-release (x86_64): GMSimpute_0.0.1.0.tgz, r-oldrel (x86_64): GMSimpute_0.0.1.0.tgz |
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These binaries (installable software) and packages are in development.
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