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Difference between revisions of "Yepez 2018 PLOS One"

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{{Publication
{{Publication
|title=Yepez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J (2018) OCR-Stats: Robust estimation and statistical testing of mitochondrial respiration activities using Seahorse XF Analyzer. PLOS One 13(7): e0199938.
|title=Yรฉpez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J (2018) OCR-Stats: Robust estimation and statistical testing of mitochondrial respiration activities using Seahorse XF Analyzer. PLOS One 13:e0199938.
|info=[https://pubmed.ncbi.nlm.nih.gov/29995917/ PMID: 29995917 Open Access]
|info=[https://pubmed.ncbi.nlm.nih.gov/29995917/ PMID: 29995917 Open Access]
|authors=Yepez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J
|authors=Yepez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J
|year=2018
|year=2018
|journal=PLOS One
|journal=PLOS One
|abstract=The accurate quantification of cellular and mitochondrial bioenergetic activity is of great interest in medicine and biology. Mitochondrial stress tests performed with Seahorse Bioscience XF Analyzers allow the estimation of different bioenergetic measures by monitoring the oxygen consumption rates (OCR) of living cells in multi-well plates. However, studies of the statistical best practices for determining aggregated OCR measurements and comparisons have been lacking. Therefore, to understand how OCR behaves across different biological samples, wells, and plates, we performed mitochondrial stress tests in 126 96-well plates involving 203 fibroblast cell lines. We show that the noise of OCR is multiplicative, that outlier data points can concern individual measurements or all measurements of a well, and that the inter-plate variation is greater than the intra-plate variation. Based on these insights, we developed a novel statistical method, OCR-Stats, that: i) robustly estimates OCR levels modeling multiplicative noise and automatically identifying outlier data points and outlier wells; and ii) performs statistical testing between samples, taking into account the different magnitudes of the between- and within-plate variations. This led to a significant reduction of the coefficient of variation across plates of basal respiration by 45% and of maximal respiration by 29%. Moreover, using positive and negative controls, we show that our statistical test outperforms the existing methods, which suffer from an excess of either false positives (within-plate methods), or false negatives (between-plate methods). Altogether, this study provides statistical good practices to support experimentalists in designing, analyzing, testing, and reporting the results of mitochondrial stress tests using this high throughput platform.
|abstract=The accurate quantification of cellular and mitochondrial bioenergetic activity is of great interest in medicine and biology. Mitochondrial stress tests performed with Seahorse Bioscience XF Analyzers allow the estimation of different bioenergetic measures by monitoring the oxygen consumption rates (OCR) of living cells in multi-well plates. However, studies of the statistical best practices for determining aggregated OCR measurements and comparisons have been lacking. Therefore, to understand how OCR behaves across different biological samples, wells, and plates, we performed mitochondrial stress tests in 126 96-well plates involving 203 fibroblast cell lines. We show that the noise of OCR is multiplicative, that outlier data points can concern individual measurements or all measurements of a well, and that the inter-plate variation is greater than the intra-plate variation. Based on these insights, we developed a novel statistical method, OCR-Stats, that: i) robustly estimates OCR levels modeling multiplicative noise and automatically identifying outlier data points and outlier wells; and ii) performs statistical testing between samples, taking into account the different magnitudes of the between- and within-plate variations. This led to a significant reduction of the coefficient of variation across plates of basal respiration by 45 % and of maximal respiration by 29 %. Moreover, using positive and negative controls, we show that our statistical test outperforms the existing methods, which suffer from an excess of either false positives (within-plate methods), or false negatives (between-plate methods). Altogether, this study provides statistical good practices to support experimentalists in designing, analyzing, testing, and reporting the results of mitochondrial stress tests using this high throughput platform.
|editor=[[Iglesias-Gonzalez J]]
}}
}}
== Cited by ==
== Cited by ==

Revision as of 06:48, 6 May 2021

Publications in the MiPMap
Yรฉpez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J (2018) OCR-Stats: Robust estimation and statistical testing of mitochondrial respiration activities using Seahorse XF Analyzer. PLOS One 13:e0199938.

ยป PMID: 29995917 Open Access

Yepez VA, Kremer LS, Iuso A, Gusic M, Kopajtich R, Konarikova E, Nadel A, Wachutka L, Prokisch H, Gagneur J (2018) PLOS One

Abstract: The accurate quantification of cellular and mitochondrial bioenergetic activity is of great interest in medicine and biology. Mitochondrial stress tests performed with Seahorse Bioscience XF Analyzers allow the estimation of different bioenergetic measures by monitoring the oxygen consumption rates (OCR) of living cells in multi-well plates. However, studies of the statistical best practices for determining aggregated OCR measurements and comparisons have been lacking. Therefore, to understand how OCR behaves across different biological samples, wells, and plates, we performed mitochondrial stress tests in 126 96-well plates involving 203 fibroblast cell lines. We show that the noise of OCR is multiplicative, that outlier data points can concern individual measurements or all measurements of a well, and that the inter-plate variation is greater than the intra-plate variation. Based on these insights, we developed a novel statistical method, OCR-Stats, that: i) robustly estimates OCR levels modeling multiplicative noise and automatically identifying outlier data points and outlier wells; and ii) performs statistical testing between samples, taking into account the different magnitudes of the between- and within-plate variations. This led to a significant reduction of the coefficient of variation across plates of basal respiration by 45 % and of maximal respiration by 29 %. Moreover, using positive and negative controls, we show that our statistical test outperforms the existing methods, which suffer from an excess of either false positives (within-plate methods), or false negatives (between-plate methods). Altogether, this study provides statistical good practices to support experimentalists in designing, analyzing, testing, and reporting the results of mitochondrial stress tests using this high throughput platform.

Cited by

  • Iglesias-Gonzalez et al (2021) Proficiency test in mt-respiration: A necessary tool for reliable and reproducible results. MitoFit Preprints 2021 (in prep).

Labels: MiParea: Instruments;methods 



Preparation: Intact cells 


Coupling state: LEAK, ROUTINE, ET 


MitoFit 2021 PT