PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-1 (1)
 

Clipboard (0)
None
Journals
Authors
Year of Publication
Document Types
1.  Merging Mixture Components for Cell Population Identification in Flow Cytometry 
Advances in Bioinformatics  2009;2009:247646.
We present a framework for the identification of cell subpopulations in flow cytometry data based on merging mixture components using the flowClust methodology. We show that the cluster merging algorithm under our framework improves model fit and provides a better estimate of the number of distinct cell subpopulations than either Gaussian mixture models or flowClust, especially for complicated flow cytometry data distributions. Our framework allows the automated selection of the number of distinct cell subpopulations and we are able to identify cases where the algorithm fails, thus making it suitable for application in a high throughput FCM analysis pipeline. Furthermore, we demonstrate a method for summarizing complex merged cell subpopulations in a simple manner that integrates with the existing flowClust framework and enables downstream data analysis. We demonstrate the performance of our framework on simulated and real FCM data. The software is available in the flowMerge package through the Bioconductor project.
doi:10.1155/2009/247646
PMCID: PMC2798116  PMID: 20049161

Results 1-1 (1)