4.1 Introduction

4.1.1 Workflow functions

Each step in the non-target workflow is performed by a function that performs the heavy lifting of a workflow step behind the scenes and finally return the results. An important goal of patRoon is to support multiple algorithms for each workflow step, hence, when such a function is called you have to specify which algorithm you want to use. The available algorithms and their characteristics will be discussed in the next sections. An overview of all functions involved in generating workflow data is shown in the table below.

Workflow step	Function	Output S4 class
Data pre-treatment	`convertMSFiles()`, `recalibrarateDAFiles()`	-
Finding features	`findFeatures()`	`features`
Grouping features	`groupFeatures()`	`featureGroups`
Suspect screening	`screenSuspects()`	`featureGroupsScreening`
Componentization	`generateComponents()`	`components`
MS peak lists	`generateMSPeakLists()`	`MSPeakLists`
Formula annotation	`generateFormulas()`	`formulas`
Compound annotation	`generateCompounds()`	`compounds`

4.1.2 Workflow output

The output of each workflow step is stored in objects derived from so called S4 classes. Knowing the details about the S4 class system of R is generally not important when using patRoon (and well written resources are available if you want to know more). In brief, usage of this class system allows a general data format that is used irrespective of the algorithm that was used to generate the data. For instance, when features have been found by OpenMS or XCMS they both return the same data format.

Another advantage of the S4 class system is the usage of so called generic functions. To put simply: a generic function performs a certain task for different types of data objects. A good example is the plotSpectrum() function which plots an (annotated) spectrum from data of MS peak lists or from formula or compound annotation:

# mslists, formulas, compounds contain results for MS peak lists and
# formula/compound annotations, respectively.

plotSpectrum(mslists, ...) # plot raw MS spectrum
plotSpectrum(formulas, ...) # plot annotated spectrum from formula annotation data
plotSpectrum(compounds, ...) # likewise but for compound annotation.

4.1.3 Overview of all functions and their output

Figure 4.1: Workflow functions and output classes.

The next sections in this chapter will further detail on how to actually perform the non-target workflow steps to generate data. The transformation product screening workflows are discussed in a separate chapter.