Amudhan Krishnaswamy-Usha, Gregory A Cooksey, Paul N Patrone
{"title":"Uncertainty Quantification in Flow Cytometry Using a Cell Sorter.","authors":"Amudhan Krishnaswamy-Usha, Gregory A Cooksey, Paul N Patrone","doi":"10.1002/cyto.a.24925","DOIUrl":null,"url":null,"abstract":"<p><p>In cytometry, it is difficult to disentangle the contributions of population variance and instrument noise toward total measured variation. Fundamentally, this is due to the fact that one cannot measure the same particle multiple times. We propose a simple experiment that uses a cell sorter to distinguish instrument-specific variation. For a population of beads whose intensities are distributed around a single peak, the sorter is used to collect beads whose measured intensities lie below some threshold. This subset of particles is then remeasured. If the variation in the measured values is only due to the sample, the second set of measurements should also lie entirely below our threshold. Any \"spillover\" is therefore due to instrument-specific effects-we demonstrate how the distribution of the post-sort measurements is sufficient to extract an estimate of the cumulative variability induced by the instrument. A distinguishing feature of our work is that we do not make any assumptions about the sources of said noise. We then show how \"local affine transformations\" let us transfer these estimates to cytometers not equipped with a sorter. We use our analysis to estimate noise for a set of three instruments and two bead types, across a range of sample flow rates. Lastly, we discuss the implications of instrument noise on optimal classification, as well as other applications.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":""},"PeriodicalIF":2.5000,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cytometry Part A","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1002/cyto.a.24925","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
In cytometry, it is difficult to disentangle the contributions of population variance and instrument noise toward total measured variation. Fundamentally, this is due to the fact that one cannot measure the same particle multiple times. We propose a simple experiment that uses a cell sorter to distinguish instrument-specific variation. For a population of beads whose intensities are distributed around a single peak, the sorter is used to collect beads whose measured intensities lie below some threshold. This subset of particles is then remeasured. If the variation in the measured values is only due to the sample, the second set of measurements should also lie entirely below our threshold. Any "spillover" is therefore due to instrument-specific effects-we demonstrate how the distribution of the post-sort measurements is sufficient to extract an estimate of the cumulative variability induced by the instrument. A distinguishing feature of our work is that we do not make any assumptions about the sources of said noise. We then show how "local affine transformations" let us transfer these estimates to cytometers not equipped with a sorter. We use our analysis to estimate noise for a set of three instruments and two bead types, across a range of sample flow rates. Lastly, we discuss the implications of instrument noise on optimal classification, as well as other applications.
期刊介绍:
Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques.
The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome:
Biomedical Instrumentation Engineering
Biophotonics
Bioinformatics
Cell Biology
Computational Biology
Data Science
Immunology
Parasitology
Microbiology
Neuroscience
Cancer
Stem Cells
Tissue Regeneration.