2022/10/03 by Christophe Vanderaa, Vanderaa, Christophe, Laurent Gatto +1
Biochemistry, Genetics and Molecular Biology · Chemistry · #Single-cell and spatial transcriptomics #Advanced Proteomics Techniques and Applications #Cell Image Analysis Techniques
paper · pdf · doi:10.48550/arxiv.2210.01020
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, 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 and list the remaining missing pieces, and conclude with lessons learned from the replication of published single-cell proteomics analyses.