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Calculating sample size requirements for temporal dynamics in single cell proteomics

Hannah Boekweg, Amanda J. Guise, Edward D. Plowey, Ryan T. Kelly, View ORCID ProfileSamuel H. Payne
doi: https://doi.org/10.1101/2020.12.09.418228
Hannah Boekweg
1Biology Department, Brigham Young University, Provo UT 82602
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Amanda J. Guise
2Translational Neuropathology, Biogen Inc., Cambridge, MA
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Edward D. Plowey
2Translational Neuropathology, Biogen Inc., Cambridge, MA
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Ryan T. Kelly
3Chemistry and Biochemistry Department, Brigham Young University, Provo UT 82602
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Samuel H. Payne
1Biology Department, Brigham Young University, Provo UT 82602
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  • ORCID record for Samuel H. Payne
  • For correspondence: sam_payne@byu.edu
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Abstract

Single cell measurements are uniquely capable of characterizing cell-to-cell heterogeneity, and have been used to explore the large diversity of cell types and physiological functions present in tissues and other complex cell assemblies. An intriguing application of single cell proteomics is the characterization of proteome dynamics during biological transitions, like cellular differentiation or disease progression. Time course experiments, which regularly take measurements during state transitions, rely on the ability to detect dynamic trajectories in a data series. However, in a single cell proteomics experiment, cell-to-cell heterogeneity complicates the confident identification of proteome dynamics as measurement variability may be higher than expected. Therefore, a critical question for these experiments is how many data points need to be acquired during the time course to enable robust statistical analysis. We present here an analysis of the most important variables that affect statistical confidence in the detection of proteome dynamics: fold-change, measurement variability, and the number of cells measured during the time course. Importantly, we show that datasets with less than 16 measurements across the time domain suffer from low accuracy and also have a high false-positive rate. We also demonstrate how to balance competing demands in experimental design to achieve a desired result.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted December 09, 2020.
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Calculating sample size requirements for temporal dynamics in single cell proteomics
Hannah Boekweg, Amanda J. Guise, Edward D. Plowey, Ryan T. Kelly, Samuel H. Payne
bioRxiv 2020.12.09.418228; doi: https://doi.org/10.1101/2020.12.09.418228
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Calculating sample size requirements for temporal dynamics in single cell proteomics
Hannah Boekweg, Amanda J. Guise, Edward D. Plowey, Ryan T. Kelly, Samuel H. Payne
bioRxiv 2020.12.09.418228; doi: https://doi.org/10.1101/2020.12.09.418228

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