Hello,
I`m a bioinformatician analyzing lipidomics experiments, which I never did before. I receive two tables with raw values from two different experiments. One table has values from 0 to 30 (Area measure), but the other has very low values from 10e-06 to 10e-11.
I used "lipidR" package in R to do all the analysis, but I don`t know how to deal with these very low values.
Is there a minimum threshold or a special way to deal with these data? Or it just background noise?
Hello, in comparison with interval 0-30 the 10e-06 to 10e-11 seems to be noise.
Mrs/Miss Barros,
Looking at the capability of the currently developed analytical instrumentation worldwide, lipidomics can be carried out precisely, accurately, selectively, sensitively, even exactly (or absolutely) by means of mass spectrometry (MS). However, there should be used our innovative own-authored (mine and my co-author's contribution according to the shown authorship, below) stochastic dynamic mass spectrometric approach to quantify experimental outcomes and model formulas. It is the only methodology currently available for exact quantification of mass spectrometric variables.
It has been tested, so far, at mixtures of analytes at pg.(mL)-1 showing linear correlation between theory and experiment within /r/ = 0.99997-1.
Please, consider references [1,2], in this context.
[1] Stochastic Dynamic Mass Spectrometric Approach to Quantify Reserpine in Solution; Bojidarka Ivanova, Michael Spiteller Analytical Chemistry Letters, 10 (2020) 703-721; Received 13 Oct 2020, Accepted 16 Dec 2020, Published online: 28 Jan 2021 Download citation https://doi.org/10.1080/22297928.2020.1865834 [2] Steroids, 164 (2020) 108750 Stochastic dynamic mass spectrometric quantification of steroids in mixture — Part II; Bojidarka Ivanova, Michael Spiteller
Perhaps, it would be useful reference [3], detailing application of MS methods to study lipids, as well.
[3] B.Ivanova, M. Spiteller, Lipidomics, Proteomics and Profiling of Low Molecular Weight Components in Brassica Napus Plant by Mass Spectrometric based Analytical Methods; In book: In Plant Science Research and Practices, M. White (Ed.) Nova Science Publishers Inc., 2016, New York, pp. 1 - 175, ISBN: 978-1-63484-227-3.
Toward the comment on Mr. Darbinyan, there should be kept in mind that our theory and model equations have a predictive capability, as well. Thus, it has capability to distinguish quantitatively between noise and MS peaks of analytes at very low concentrations up to the instrumental detection limits of fmol and attomol levels. In the latter context, please, consider reference [4].
[4] Bojidarka Ivanova und Michael Spiteller A stochastic dynamic mass spectrometric diffusion method and its application to 3D structural analysis of the analytes; Reviews in Analytical Chemistry, 38 (2019) 20190003; DOI: https://doi.org/10.1515/revac-2019-0003
If you have any questions, regarding, the theory itself or its application to study lipids quantitatively, then, please, do not hesitate to ask them, herein. They shall be addressed, accordingly.
Perhaps they're different units or from different instruments? e.g. concentration vs peak area... what standards are involved?
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