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The goal of lfproQC R package is to provide an optimal combination ofnormalization and imputation methods for the label-free proteomicsexpression dataset.
You can install the development version of lfproQC fromGitHub with:
# install.packages("devtools")devtools::install_github("kabilansbio/lfproQC",build_manual=TRUE,build_vignette=TRUE)
This is a basic example for finding the best combinations ofnormalization and imputation method for the label-free proteomicsexpression dataset:
library(lfproQC)## basic example code with the example dataset and data groupsyeast<- best_combination(yeast_data,yeast_groups,data_type="Protein")yeast$`Best combinations`#> PCV_best_combination PEV_best_combination PMAD_best_combination#> 1 rlr_knn, rlr_lls vsn_lls rlr_lls
The overall workflow for using the ‘lfproQC’ package
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Quality Control for Label-Free Proteomics Expression Data
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