data analysis;
mass spectrometry;
proteomics;
reproducible research;
single-cell;
HIGH-THROUGHPUT;
DATA SETS;
QUANTIFICATION;
STRATEGY;
D O I:
10.1002/cpz1.658
中图分类号:
Q5 [生物化学];
学科分类号:
071010 ;
081704 ;
摘要:
Sound data analysis is essential to retrieve meaningful biological information from single-cell proteomics experiments. This analysis is carried out by computational methods that are assembled into workflows, and their implementations influence the conclusions that can be drawn from the data. In this work, we explore and compare the computational workflows that have been used over the last four years and identify a profound lack of consensus on how to analyze single-cell proteomics data. We highlight the need for benchmarking of computational workflows and standardization of computational tools and data, as well as carefully designed experiments. Finally, we cover the current standardization efforts that aim to fill the gap, list the remaining missing pieces, and conclude with lessons learned from the replication of published single-cell proteomics analyses. (c) 2023 Wiley Periodicals LLC.