Publications by authors named "Annika Tostengard"
Article Synopsis
- Extracted ion chromatograms (XIC) are essential for analyzing mass spectrometry data, but various algorithms have differing performances in distinguishing real signals from noise.
- While many qualitative opinions exist on these algorithms, there has been a lack of quantitative evaluations due to the absence of a reliable ground truth dataset.
- Using a newly created dataset of manually extracted XICs from 48 human proteins, this study assesses the performance of popular algorithms like MaxQuant and MZMine2, revealing significant variations in their effectiveness depending on parameter settings, with most recovering over 10,000 true positive XICs.
Modern label-free quantitative mass spectrometry workflows are complex experimental chains for devising the composition of biological samples. With benchtop and in silico experimental steps that each have a significant effect on the accuracy, coverage, and statistical significance of the study result, it is crucial to understand the efficacy and biases of each protocol decision. Although many studies have been conducted on wet lab experimental protocols, postacquisition data processing methods have not been adequately evaluated in large part due to a lack of available ground truth data.
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