README.md

MetNormalizer

Introduction

MetNormalizer is used to normalize large scale metabolomics data. weblin:http://link.springer.com/article/10.1007/s11306-016-1026-5?no-access=true

Installation

if(!require(devtools)){
install.packages("devtools")
}
devtools::install_github("jaspershen/MetNormalizer")

Usage

The new version (1.3.01) needs two files named 'data.csv' and 'sample.info.csv'.

data

Data is used to provied the metabolomics data. This must be a .csv format and named as 'data.csv'. The first column must be the names of peaks (named as 'name'). The second column must be the mass to change of peaks (named as 'mz'). The third column must be retention time of peaks (named as 'rt'). Other columns are intensity of samples.

Figure 1 Data

sample.info

sample.info is used to provied the information of samples. This must be a .csv format and named as 'sample.info.csv'. The first column must be the names of samples (named as 'sample.name'). The second column must be the injection order of samples (named as 'injection.order'). The third column must be class of samples (named as 'class', and subject samples should be noted as 'Subject' and QC samples should be noted as 'QC').

Figure 2 sample.info

Note

Running

Please place the 'data.csv' and 'sample.info.csv' in a folder and set this folder as your work directory.

setwd("xxx\xxx\xxx")
library(MetNormalizer)
MetNormalizer(minfrac.qc = 0,
              minfrac.sample = 0, 
              normalization.method = "svr",
              multiple = 5)

Parameters



jaspershen/MetNormalizer documentation built on April 9, 2018, 12:09 p.m.