Guiding the choice of informatics software and tools for lipidomics research applications

Abstract

links, descriptions, video tutorials, and contact details for software developers. The new tool comprehensively covers the seven major areas in lipidomics data processing, as follows: (1) lipid-oriented databases; (2) MS data repositories; (3) analysis of targeted lipidomics datasets; (4) lipid identification and (5) quantification from untargeted lipidomics datasets; (6) statistical analysis and visualization; and (7) data integration solutions (Fig. 2). To support informed decision making by lipidomics analysts, for each software, a short description is provided, highlighting the main functionalities and the areas of applications, followed by the specific features listed under 'Technical information' and 'Task specific information' tabs (Figs. 3 and 4). Additionally, users can review simplified, tabular representations of the available functions for each tool in a given section by using the 'Tools Overview' tab.In the 'Technical information' section, users can view the type of the license under which the tool is distributed, the availability of desktop and/or web-based interfaces, data input/output formats, and compatibility with different operating systems (for example, Windows, Linux, macOS). There is also information accessible via clickable links, which allow the downloading of the tool together with related documentation, user guides, and training datasets. Additional fields list how to use the tool through the command line or via API interfaces for advanced users wishing to construct their own customized pipelines. 'Task specific information' tabs navigate users to pages describing functionalities of the software for particular tasks covering the seven areas outlined above (Figs. 1 and 2). Some comprehensive tools have multiple functions integrated into one combined package and can be configured for a wide range of workflows. These tools are assigned to each task with associated descriptions accordingly, and the list of tools is shown in Table 1. In the next section, we provide more details about each area and its associated software and tools.

Chewing the fat: How lipidomics is changing our understanding of human health and disease in 2022

“…Specialised tools, such as LipidCreator 136 and METLIN‐MRM, 137 can aid experimental method development and processing steps. In comparison to untargeted data processing (discussed below), the post‐acquisition processing of targeted data is relatively straightforward using open‐access tools, such as Skyline 138 or XCMS‐MRM, 137 or vendor software, such as TargetLynx, 139 that can automate peak integration, relative and absolute quantification, and evaluate data quality 140 …”

An overview of food lipids toward food lipidomics

“…Such measurements usually create a large amount of data and often show a lack in sensitivity in contrast to targeted approaches. These data are usually aided by bioinformatics tools for lipidomics data analysis (Ni et al., 2022). Furthermore, the reproducibility, especially in the case of data‐dependent acquisition, may not always be given and can be a drawback of such methods.…”

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“… 8 , 9 (iii) An online tool developed by LIPID MAPS and EpiLipidNet for informatics resources was this week published in Nature Methods ( link ). 10 …”