Avant-garde: an automated data-driven DIA data curation tool

Abstract

Data-Independent Acquisition (DIA) is a technique that promises to comprehensively detect and quantify all peptides above an instrument's limit of detection. Several software tools to analyze DIA data have been developed in recent years. However, several challenges still remain, like confidently identifying peptides, defining integration boundaries, dealing with interference for selected transitions, and scoring and filtering of peptide signals in order to control false discovery rates. In practice, a visual inspection of the signals is still required, which is impractical with large datasets. Avant-garde is a new tool to refine DIA (and PRM) by removing interfered transitions, adjusting integration boundaries and scoring peaks to control the FDR. Unlike other tools where MS runs are scored independently from each other, Avant-garde uses a novel data-driven scoring strategy. DIA signals are refined by learning from the data itself, using all measurements in all samples together to achieve the best optimization. We evaluated the performances of Avant-garde with a calibrated sample using spiked-in standards in a complex background, a phospho-enriched dataset (Abelin et al , 2016), and two complex hybrid proteome samples for benchmarking DIA software tools. The results clearly showed that Avant-garde is capable of improving the selectivity, accuracy, and reproducibility of the quantification results in very complex biological matrices. We have further shown that it can evaluate the suitability of a peak to be used for quantification reaching the same levels of selectivity, accuracy, and reproducibility obtained with manual validation.

MaxDIA enables library-based and library-free data-independent acquisition proteomics

“…In recent years, several researchers have worked on approaches to remove interferences and improve the selection of transitions in DIA analysis [40][41][42][43] . Although this approach to improving quantification has its merits, in this study we followed a different strategy with MaxLFQ to obtain high accuracy on the level of protein groups.…”

Cloud-based DIA data analysis module for signal refinement improves accuracy and throughput of large datasets

“…The relative quantification of the two datasets matched (Supplementary figure 2) demonstrating that the two implementations of AvG provide the same results for the relative quantification across a broad concentration range. We next applied the AvG Terra workflow to a triple-proteome sample consisting of four mixture samples of three complex proteomes (Human, E. Coli and Yeast) that was described in the original AvG paper 11 . The results of this evaluation show excellent accuracy, as the measured ratios matched very closely the known protein ratios (Supplementary Figure 3, Supplementary Figure 4 and supplementary Table 1).…”

“…We previously developed Avant-garde (AvG) 11 , a tool for automated signal refinement of DIA and other targeted mass spectrometry data. AvG is designed to work alongside existing tools for peptide detection 8,[12][13][14][15] to address the reliability and quantitative suitability of signals extracted for the identified peptides.…”

Quality Assessment of Untargeted Analytical Data in a Large-Scale Metabolomic Study

“…Automation of peak processing has been used to measure as many peaks as possible, and various processing tools have been developed to automatically extract peaks from raw data [ 14 , 15 ]. However, it has been argued that visual inspection and manual curation of the peaks may be necessary to ensure their quality [ 16 , 17 ].…”