Package: GMSimpute 0.0.1.0

GMSimpute: Generalized Mass Spectrum Missing Peaks Abundance Imputation

GMSimpute implements the Two-Step Lasso (TS-Lasso) and compound minimum to recover the abundance of missing peaks in mass spectrum analysis. TS-Lasso is a label-free 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.

Authors:Qian Li [aut, cre]

GMSimpute_0.0.1.0.tar.gz
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GMSimpute.pdf |GMSimpute.html✨
GMSimpute/json (API)

# Install 'GMSimpute' in R:
install.packages('GMSimpute', repos = c('https://qianli10000.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/qianli10000/gmsimpute/issues

Datasets:
  • replicates - Raw mass spectrum proteomics log abundance for 4 pairs of technical replicates.
  • tcga.bc - Raw mass spectrum metabolomics data for TCGA breast cancer study.
  • tcga.bc.full - A subset of mass spectrum metabolomics data for TCGA breast cancer study without missing peaks.

On CRAN:

Conda:

3.20 score 32 scripts 185 downloads 4 exports 32 dependencies

Last updated from:c0f55aa72c. Checks:6 ERROR, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64ERROR153
source / vignettesOK168
linux-release-x86_64ERROR147
macos-devel-arm64ERROR122
macos-release-arm64ERROR139
windows-develERROR107
windows-releaseERROR96
wasm-releaseOK109

Exports:GMS.LassoMAR.estmissing.simTS.Lasso

Dependencies:clicodetoolscpp11farverforeachggplot2glmnetgluegtableisobanditeratorslabelinglatticelifecyclemagrittrMatrixplyrR6RColorBrewerRcppRcppEigenreshape2rlangS7scalesshapestringistringrsurvivalvctrsviridisLitewithr