Orbitrap noise structure and method for noise unbiased multivariate analysis
Abstract Orbitrap mass spectrometry is widely used in the life-sciences. However, like all mass spectrometers, non-uniform (heteroscedastic) noise introduces bias in multivariate analysis complicating data interpretation. Here, we study the noise structure of an Orbitrap mass analyser integrated int...
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Nature Portfolio
2025-07-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-61542-2 |
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| author | Michael R. Keenan Gustavo F. Trindade Alexander Pirkl Clare L. Newell Yuhong Jin Konstantin Aizikov Andreas Dannhorn Junting Zhang Lidija Matjačić Henrik Arlinghaus Anya Eyres Rasmus Havelund Richard J. A. Goodwin Zoltan Takats Josephine Bunch Alex P. Gould Alexander Makarov Ian S. Gilmore |
| author_facet | Michael R. Keenan Gustavo F. Trindade Alexander Pirkl Clare L. Newell Yuhong Jin Konstantin Aizikov Andreas Dannhorn Junting Zhang Lidija Matjačić Henrik Arlinghaus Anya Eyres Rasmus Havelund Richard J. A. Goodwin Zoltan Takats Josephine Bunch Alex P. Gould Alexander Makarov Ian S. Gilmore |
| author_sort | Michael R. Keenan |
| collection | DOAJ |
| description | Abstract Orbitrap mass spectrometry is widely used in the life-sciences. However, like all mass spectrometers, non-uniform (heteroscedastic) noise introduces bias in multivariate analysis complicating data interpretation. Here, we study the noise structure of an Orbitrap mass analyser integrated into a secondary ion mass spectrometer (OrbiSIMS). Using a stable primary ion beam to provide a well-controlled source of ions from a silver sample, we find that noise has three characteristic regimes: at low signals the Orbitrap detector noise and a censoring algorithm dominates; at intermediate signals counting noise specific to the ion emission process is most significant; and at high signals additional sources of measurement variation become important. Using this understanding, we developed a generative model for Orbitrap data that accounts for the noise distribution and introduce a scaling method, termed WSoR, to reduce the effects of noise bias in multivariate analysis. We compare WSoR performance with no-scaling and existing scaling methods for three biological imaging data sets including drosophila central nervous system, mouse testis and a desorption electrospray ionisation (DESI) image of a rat liver. WSoR consistently performed best at discriminating chemical information from noise. The performance of the other methods varied on a case-by-case basis, complicating the analysis. |
| format | Article |
| id | doaj-art-0473844ed1a24347a2808eb46962608a |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-0473844ed1a24347a2808eb46962608a2025-08-20T03:46:28ZengNature PortfolioNature Communications2041-17232025-07-0116111710.1038/s41467-025-61542-2Orbitrap noise structure and method for noise unbiased multivariate analysisMichael R. Keenan0Gustavo F. Trindade1Alexander Pirkl2Clare L. Newell3Yuhong Jin4Konstantin Aizikov5Andreas Dannhorn6Junting Zhang7Lidija Matjačić8Henrik Arlinghaus9Anya Eyres10Rasmus Havelund11Richard J. A. Goodwin12Zoltan Takats13Josephine Bunch14Alex P. Gould15Alexander Makarov16Ian S. Gilmore17IndependentNational Physical Laboratory, NiCE-MSIIONTOF GmbHThe Francis Crick InstituteThe Francis Crick InstituteThermo Fisher ScientificAstraZenecaNational Physical Laboratory, NiCE-MSINational Physical Laboratory, NiCE-MSIIONTOF GmbHNational Physical Laboratory, NiCE-MSINational Physical Laboratory, NiCE-MSIAstraZenecaImperial College LondonNational Physical Laboratory, NiCE-MSIThe Francis Crick InstituteThermo Fisher ScientificNational Physical Laboratory, NiCE-MSIAbstract Orbitrap mass spectrometry is widely used in the life-sciences. However, like all mass spectrometers, non-uniform (heteroscedastic) noise introduces bias in multivariate analysis complicating data interpretation. Here, we study the noise structure of an Orbitrap mass analyser integrated into a secondary ion mass spectrometer (OrbiSIMS). Using a stable primary ion beam to provide a well-controlled source of ions from a silver sample, we find that noise has three characteristic regimes: at low signals the Orbitrap detector noise and a censoring algorithm dominates; at intermediate signals counting noise specific to the ion emission process is most significant; and at high signals additional sources of measurement variation become important. Using this understanding, we developed a generative model for Orbitrap data that accounts for the noise distribution and introduce a scaling method, termed WSoR, to reduce the effects of noise bias in multivariate analysis. We compare WSoR performance with no-scaling and existing scaling methods for three biological imaging data sets including drosophila central nervous system, mouse testis and a desorption electrospray ionisation (DESI) image of a rat liver. WSoR consistently performed best at discriminating chemical information from noise. The performance of the other methods varied on a case-by-case basis, complicating the analysis.https://doi.org/10.1038/s41467-025-61542-2 |
| spellingShingle | Michael R. Keenan Gustavo F. Trindade Alexander Pirkl Clare L. Newell Yuhong Jin Konstantin Aizikov Andreas Dannhorn Junting Zhang Lidija Matjačić Henrik Arlinghaus Anya Eyres Rasmus Havelund Richard J. A. Goodwin Zoltan Takats Josephine Bunch Alex P. Gould Alexander Makarov Ian S. Gilmore Orbitrap noise structure and method for noise unbiased multivariate analysis Nature Communications |
| title | Orbitrap noise structure and method for noise unbiased multivariate analysis |
| title_full | Orbitrap noise structure and method for noise unbiased multivariate analysis |
| title_fullStr | Orbitrap noise structure and method for noise unbiased multivariate analysis |
| title_full_unstemmed | Orbitrap noise structure and method for noise unbiased multivariate analysis |
| title_short | Orbitrap noise structure and method for noise unbiased multivariate analysis |
| title_sort | orbitrap noise structure and method for noise unbiased multivariate analysis |
| url | https://doi.org/10.1038/s41467-025-61542-2 |
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