mQTL.NMR (version 1.6.0)

mQTL.NMR-package: Metabolomic Quantitative Trait Locus mapping for 1H NMR data

Description

mQTL.NMR provides a complete mQTL analysis pipeline for 1H NMR data. Distinctive features include normalisation using most-used approaches, peak alignment using RSPA approach, dimensionality reduction using SRV and binning approaches, and mQTL analysis for animal and human cohorts.

Details

Package:

mQTL.NMR

Type:

Package

Version:

0.99.2

Link:

http://www.ican-institute.org/tools

Date:

2014-05-19

License:

Artistic-2.0

Main fucntions:

• format_mQTL: generates the proper format of animal crosses data
• format_mGWA: generates the proper format of human data
• align_mQTL: peak alignment
• normalise_mQTL: normalisation of metabolomic data using different approaches (Probabilistic quotient, constant sum,...)
• pre_mQTL: dimension reduction by statistical recoupling of variables or bining
• process_mQTL: computes LODs using extended Haley-Knott method for animal crosses
• process_mGWA: computes p-values using a standard linear regression approach for human
• post_mQTL: plots the results of a given run
• summary_mQTL: provides the results as a table
• simple.plot: Plots a region of NMR profile
• SRV.plot: Plots the regions identified by SRV in NMR profiles
• ppersp: Plot 3-D profile of LODs as function of genomic position and chemical shift
• pplot: Plot a color scale layer
• Top_SRV.plot: Plot top SRV clusters for structural assignment
• circle_mQTL: Plot a circular genome-metabolome plot

References

- L. HEDJAZI, D. GAUGUIER, P. ZALLOUA, J. NICHOLSON, M-E DUMAS and J-B CAZIER, mQTL-NMR: an integrated suite for genetic mapping of quantitative variations of 1H NMR-based metabolic profiles, Analytical Chemistry, 2015, doi: 10.1021/acs.analchem.5b00145.

Examples

# Download data files

load_datafiles()

# Format data

format_mQTL(phenofile,genofile,physiodat,cleandat,cleangen)

# Constant Sum normlisation
nmeth<-'CS'
normalise_mQTL(cleandat,CSnorm,nmeth)

# Alignment
align_mQTL(CSnorm,aligdat)

# Dimensionality reduction
met="rectangle" # choose the statistical summarizing measure ("max","sum","trapez",...)
RedMet="SRV" # reduction method ("SRV" or "bin")

pre_mQTL(aligdat, reducedF, RedMet="SRV",met, corrT=0.9)

# mQTL mapping
results<- list() # a list to stock the mQTL mapping results
nperm<- 0 # number of permutations if required
results<-process_mQTL(reducedF, cleangen, nperm)

## Post-Process
post_mQTL(results)

## Summarize 
redfile<-"rectangle_SRV.ppm"
summary_mQTL(results,redfile,T=8)

#plot circular genome
circle_mQTL(results, Th=8,spacing=0)

## visualisation and metabolite identification
#plot NMR profile
simple.plot(file=cleandat,lo=3.02,hi=3.08,k=1:20,title="NMR profile") 

#plot SRV regions
SRV.plot(file1=cleandat,file2=rectangle_SRV,lo=3.02,hi=3.08,k=1:20,title="Cluster plot")

#plot lod for the region of interest
SRV_lod.plot(results,rectangle_SRV,Th=1)

#plot top lod SRV regions
Top_SRV.plot(file1=cleandat,file2=rectangle_SRV,results=results,met=met,intMeth="mean")