Initial recommendations for performing, benchmarking and reporting single-cell proteomics experiments.
Laurent GattoRuedi AebersoldJuergen CoxVadim DemichevJason DerksEdward EmmottAlexander M FranksAlexander R IvanovRyan T KellyLuke KhouryAndrew LeducMichael J MacCossPeter NemesDavid H PerlmanAleksandra A PetelskiChristopher M RoseErwin M SchoofJennifer E Van EykChristophe VanderaaJohn Yates IiiNikolai SlavovPublished in: Nature methods (2023)
Analyzing proteins from single cells by tandem mass spectrometry (MS) has recently become technically feasible. While such analysis has the potential to accurately quantify thousands of proteins across thousands of single cells, the accuracy and reproducibility of the results may be undermined by numerous factors affecting experimental design, sample preparation, data acquisition and data analysis. We expect that broadly accepted community guidelines and standardized metrics will enhance rigor, data quality and alignment between laboratories. Here we propose best practices, quality controls and data-reporting recommendations to assist in the broad adoption of reliable quantitative workflows for single-cell proteomics. Resources and discussion forums are available at https://single-cell.net/guidelines .
Keyphrases
- single cell
- data analysis
- electronic health record
- induced apoptosis
- mass spectrometry
- tandem mass spectrometry
- rna seq
- clinical practice
- liquid chromatography
- cell cycle arrest
- healthcare
- high throughput
- big data
- primary care
- high resolution
- high performance liquid chromatography
- ultra high performance liquid chromatography
- adverse drug
- gas chromatography
- simultaneous determination
- mental health
- endoplasmic reticulum stress
- oxidative stress
- ms ms
- emergency department
- machine learning
- signaling pathway
- quality improvement
- cell death
- risk assessment
- climate change