Tools for computational processing of LC–MS datasets: A user's perspective

Liquid chromatography–mass spectrometry (LC–MS) profiling of clinical samples for quantifying absolute ion abundances of peptides and proteins has emerged as a promising approach. Quantitation of changes in protein abundance of large number of samples is challenging and requires automatic processing means. The development of data analysis software is laborious and time-consuming. Fortunately, freely available tools have been recently introduced, which incorporate algorithms for visualization and data processing and allow the user to embed external routines for data analysis. A relevant issue related to the design and evaluation of such tools concerns usability. Properties such as easy access, large datasets management, modularity, integration with other tools, etc, are important for performing large-scale integrative data analysis with methods and visual techniques from different (possibly integrated) tools. In this paper, we consider four freely available tools recently introduced in top international journals in order to identify a list of such usability descriptors. We propose 10 descriptors that can be used both as guidelines when developing new tools and as parameters for assessing usability of existing tools. The considered tools show satisfactory usability properties, and the most recent tools exhibit improved flexibility, indicating a trend towards the design of tools that give the user a more central role in the selection, use and integration of methods and tools.