Normalization of Mass Cytometry Data with Bead Standards
- Normalization Software
- Experiment Overview
- Overview Illustration
- Figure 1a: Bead singlet identification
- Figure 1b: Bead single identification
- Figure 2: Bead smoothing and normalization
- Figure 3: Selecting biological signals for validation of bead-based normalization
- Figure 4: Distributions of surface markers before and after bead normalization
- Figure 5a:Normalization stabilizes surface marker intensities over time and maintains multivariate correlations between markers
- Figure 5b:Normalization stabilizes surface marker intensities over time and maintains multivariate correlations between markers
- Figure 6a: Normalization of data spanning multiple days and instruments
- Figure 6b: Normalization of data spanning multiple days and instruments
- Figure 6c: Normalization of data spanning multiple days and instruments
Mass cytometry uses atomic mass spectrometry combined with isotopically pure reporter elements to currently measure as many as 40 parameters per single cell. As with any quantitative technology, there is a fundamental need for quality assurance and normalization protocols. In the case of mass cytometry, the signal variation over time due to changes in instrument performance combined with intervals between scheduled maintenance must be accounted for and then normalized. Here, samples were mixed with polystyrene beads embedded with metal lanthanides, allowing monitoring of mass cytometry instrument performance over multiple days of data acquisition. The protocol described here includes simultaneous measurements of beads and cells on the mass cytometer, subsequent extraction of the bead-based signature, and the application of an algorithm enabling correction of both short- and long-term signal fluctuations. The variation in the intensity of the beads that remains after normalization may also be used to determine data quality. Application of the algorithm to a one-month longitudinal analysis of a human peripheral blood sample reduced the range of median signal fluctuation from 4.9-fold to 1.3-fold.
The goal of this study was to develop a protocol and algorithm that uses internal bead standards to normalize mass cytometry data, thus enabling the quantitative comparison of samples acquired at different times.
DVS Sciences, Inc. CyTOF™ Mass Cytometer
Figure 5a:Normalization stabilizes surface marker intensities over time and maintains multivariate correlations between markers
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