knitr::opts_chunk$set( collapse = TRUE, comment = "#>", # fig.width = 7, # fig.height = 5, warning = FALSE, message = TRUE )
You can install MetNormalizer
from Github.
# Install `MetNormalizer` from GitHub if(!require(devtools)){ install.packages("devtools") } devtools::install_github("jaspershen/MetNormalizer")
We use the demo data in demoData
package to show how to use MetNormalizer
. Please install it first.
devtools::install_github("jaspershen/demoData")
library(demoData) library(MetNormalizer) path <- system.file("MetNormalizer", package = "demoData") file.copy(from = path, to = ".", overwrite = TRUE, recursive = TRUE) new.path <- file.path("./MetNormalizer")
MetNormalizer
metNor( ms1.data.name = "data.csv", sample.info.name = "sample.info.csv", minfrac.qc = 0, minfrac.sample = 0, optimization = TRUE, multiple = 5, threads = 4, path = new.path )
All the results will be placed in the folder named as svr_normalization_result
.
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