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A new open access article published in Nature Communications illustrates how IROA and the Lorenzi lab at MD Anderson (Houston, Texas) used the IROA TruQuant Workflow to correct Raw mass spectral signal for instrumental and source ion losses and then used the Suppression-Corrected signal to effect a very effective sample-to-sample normalization.
This publication demonstrates that mass spectral technical variances can be corrected, and when a a Dual MSTUS normalization is applied the resulting dataset, which has reduced error, has higher statistical power. Enhanced results support better clinical biomarker discovery (click image below for the article).
Mass spectrometry has excellent sensitivity and can be quite useful in identification of underlying peaks found; however, it never has been quantitative. The ionization rates are incredibly sensitive to source conditions and will differ from run to run. The use of the IROA protocols allows one to calculate the extent of these suppression losses and restore original signal. Once the suppression losses are corrected for a MSTUS algorithm is extremely effective at normalization in order to account for sample-to-sample variances. In this case a Dual MSTUS normalization may be applied that means the normalization will be consistent across samples and time. With the correction for the variances introduced by both instrumental losses and sample-to-samples variances the dataset has significantly better data resolution.
Have you considered the impact signal losses and other signal variances on your dataset? Discover how this TruQuant workflow can deliver reproducible quantitative data across days, weeks, or years of analyses.
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