assignment-methods: Molecular formula assignment methods

In jasenfinch/MFassign: Molecular Formula Assignment For High Resolution ESI-MS Based Metabolomics Data

Molecular formula assignment methods

Description

These methods provide access to performing the individual steps of the molecular formula assignment approach. See Details for more information of when it is best to use these instead of assignMFs().

Usage

calcCorrelations(assignment)

## S4 method for signature 'Assignment'
calcCorrelations(assignment)

addIsoAssign(assignment)

## S4 method for signature 'Assignment'
addIsoAssign(assignment)

transformationAssign(assignment)

## S4 method for signature 'Assignment'
transformationAssign(assignment)

calcRelationships(assignment)

## S4 method for signature 'Assignment'
calcRelationships(assignment)

Arguments

assignment

an object of S4 class Assignment

Details

In circumstances where the molecular formula assignment approach has high memory requirements, such as where there are many correlations (> 2 million) or many high m/z (>700), it may be preferable to perform the assignment steps separately as opposed to using assignMFs(). This can reduce the memory overheads required to successfully assign molecular formulas to the data and also enable the possibility of objects to be saved and/or unloaded between the assignment steps where needed.

Value

An object of S4 class Assignment containing molecular formula assignments.

Examples

plan(future::sequential)
p <- assignmentParameters('FIE-HRMS')

mf_assignments <- assignment(feature_data,p)

mf_assignments <- mf_assignments %>% 
   calcCorrelations() %>% 
   calcRelationships() %>% 
   addIsoAssign() %>% 
   transformationAssign()

mf_assignments

jasenfinch/MFassign documentation built on Feb. 2, 2024, 11:21 a.m.