mQTL.NMR-package {mQTL.NMR} | R Documentation

## 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

### Author(s)

Lyamine Hedjazi and Jean-Baptiste Cazier

Maintainer: Lyamine Hedjazi <mqtl@ican-institute.org>

### 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")

[Package mQTL.NMR version 1.14.0 Index]