Metabo_data_analyzer: Metabo_data_analyzer

In lucanard/GH_OMIC: The package deconvolutes Q-exactive data in matrix-like data using Yann Guitton scripts and then cleans the dataset eliminating redundant peaks

Description

The function transforms you raw mzML data files in a deconvoluted peaklist eliminating also the the redundant informations

Usage

Metabo_data_analyzer(datapath, pathresult = NULL, author = "LNA", use_IPO = FALSE, ret_corvar=FALSE, intvalpar="into", center=NULL, normalization=TRUE, NomRapport = NULL, grouping_mode, no_conditioning_QC = "ON", list_conQC= "NULL", RT_max)

Arguments

datapath	the path source where is the data to analyze
pathresult	the path where to store the analyzed data
author	the name of project author. Default to Luca
use_IPO	either use IPO or not to determine the best wcms parameters for peak picking. (Not available yet)
ret_corvar	chose the method to align the samples between "density" and "obiwarp"
intvalpar	what kind of peak measurement should the algorithm use? default to IPO
centerQC	should the obiwarp method centered to a specific QC sample
normalization	should the sample batch normalized?
NomRapport	what is the name of Rapport? default to a name obtained from the datapath
grouping_mode	what kind of grouping mode should CAMERA use to determine the pseudospectra? chose between EIC_corr or area_corr
no_conditioning_QC	should be conditioning QC erased from the normalization process? Default set to yes
list_conQC	list of conditioning QC. If null, the algorithm will try to determine what are the conditioning QCs
RT_max	What is the limit of RT to consider a peak included in the peaklist?

Value

peaky

Author(s)

Luca Narduzzi "[e-mail]"

Examples

peaky <- Metabo_data_analyzer(datapath = datapathy, grouping_mode = "area_corr", RT_max = 17)

lucanard/GH_OMIC documentation built on Nov. 9, 2020, 6:23 p.m.