Strategies to enable large-scale proteomics for reproducible research
Details
Publication Year 2020-07-30, Volume 11, Issue #1, Page 3793
Journal Title
Nature Communications
Publication Type
Journal Article
Abstract
Reproducible research is the bedrock of experimental science. To enable the deployment of large-scale proteomics, we assess the reproducibility of mass spectrometry (MS) over time and across instruments and develop computational methods for improving quantitative accuracy. We perform 1560 data independent acquisition (DIA)-MS runs of eight samples containing known proportions of ovarian and prostate cancer tissue and yeast, or control HEK293T cells. Replicates are run on six mass spectrometers operating continuously with varying maintenance schedules over four months, interspersed with ~5000 other runs. We utilise negative controls and replicates to remove unwanted variation and enhance biological signal, outperforming existing methods. We also design a method for reducing missing values. Integrating these computational modules into a pipeline (ProNorM), we mitigate variation among instruments over time and accurately predict tissue proportions. We demonstrate how to improve the quantitative analysis of large-scale DIA-MS data, providing a pathway toward clinical proteomics.
Publisher
NPG
WEHI Research Division(s)
Bioinformatics
PubMed ID
32732981
Open Access at Publisher's Site
https://doi.org/10.1038/s41467-020-17641-3
Rights Notice
Refer to copyright notice on published article.


Creation Date: 2020-08-05 11:11:27
Last Modified: 2020-08-05 04:37:09
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