An easy to use tool provides graphical user interface for quality control based shift signal correction, integration of metabolomic data from multi-batch experiments, and the comprehensive statistic analysis in non-targeted or targeted metabolomics.
Link to CRAN: https://cran.r-project.org/web/packages/statTarget/
The main GUI of statTarget has two basic components. The first is shift correction. It includes quality control-based robust LOESS signal correction (QC-RLSC) that is a widely accepted method for quality con trol based signal correction and integration of metabolomic data from multiple analytical batches (Dunn WB., et al. 2011; Luan H., et al. 2015).
statTarget - Shift Correction provide QC-RLSC algorithm that fit the QC data, and each metabolites in the true sample will be normalized to the QC sample. Additionally, LOESS based generalised cross-validation (GCV) would be automatically applied to avoid overfitting of the observed data, when the QCspan was set at 0 (Default value).
statTarget - Statistical Analysis provide features including Data preprocessing, Data descriptions, Multivariate statistics analysis and Univariate analysis.
Data preprocessing : 80-precent rule, glog transformation, KNN imputation, Median imputation and Minimum values imputation.
Data descriptions : Mean value, Median value, Sum, Quartile, Standard derivatives, etc.
Multivariate statistics analysis : PCA, PLSDA, VIP, Random forest.
Univariate analysis : Student T-test, Shapiro-Wilk normality test and Mann-Whitney tests.
Biomarkers analysis : ROC, Odd ratio, P-value, and Volcano plot.
Download the [statTarget tutorial](https://github.com/13479776/Picture/blob/master/work flow.pptx "statTarget tutorial .pptx") and example data .
Dependent on R (>= 3.3.0)
Packages should be installed:
randomForest,plyr,pROC,rrcov,RGtk2,pls,gWidgets2,gWidgets2RGtk2,pdist,impute
1 If you did not install the R software yet,you can download R >= 3.3.0 from https://www.r-project.org
2 Install the package "statTarget" at the CRAN
For Windows PC, copy this code into R
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
install.packages("statTarget")
library(statTarget) ## Execute statTarget
For mac PC, the package "statTarget" requires X11 support being installed. XQuartz could be installed. Download it from https://www.xquartz.org
Copy this code into R
source("https://bioconductor.org/biocLite.R")
biocLite("impute")
install.packages("statTarget")
library(statTarget) ## Execute statTarget
4 Input data and run (See the example data)
Hemi Luan, hemi.luan@gmail.com
Hemi Luan (2016). statTarget: Statistical Analysis of Metabolite Profile. R package version 1.2.2.
Dunn, W.B., et al.,Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry. Nature Protocols 2011, 6, 1060-83.
Luan H., LC–MS-Based Urinary Metabolite Signatures in Idiopathic Parkinson’s Disease. J Proteome Res., 2015, 14 (1),467–478.
Luan H., Non-targeted metabolomics and lipidomics LC–MS data from maternal plasma of 180 healthy pregnant women. GigaScience 2015 4:16