A New Evaluation Metric for Quantitative Accuracy of LC–MS/MS-Based Proteomics with Data-Independent Acquisition

Data-independent acquisition (DIA)
has improved the identification
and quantitation coverage of peptides and proteins in liquid chromatography–tandem
mass spectrometry-based proteomics. However, different DIA data-processing
tools can produce very different identification and quantitation results
for the same data set. Currently, benchmarking studies of DIA tools
are predominantly focused on comparing the identification results,
while the quantitative accuracy of DIA measurements is acknowledged
to be important but insufficiently investigated, and the absence of
suitable metrics for comparing quantitative accuracy is one of the
reasons. A new metric is proposed for the evaluation of quantitative
accuracy to avoid the influence of differences in false discovery
rate control stringency. The part of the quantitation results with
high reliability was acquired from each DIA tool first, and the quantitative
accuracy was evaluated by comparing quantification error rates at
the same number of accurate ratios. From the results of four benchmark
data sets, the proposed metric was shown to be more sensitive to discriminating
the quantitative performance of DIA tools. Moreover, the DIA tools
with advantages in quantitative accuracy were consistently revealed
by this metric. The proposed metric can also help researchers in optimizing
algorithms of the same DIA tool and sample preprocessing methods to
enhance quantitative accuracy.