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National Repository of Grey Literature 1 records found  Search took 0.00 seconds. 
Optimizations and applications of non-linear spectral unmixing in flow cytometry
 Nemec, Matěj ; Musil, Jan (advisor) ; Stuchlý, Jan (referee)
Recent advances in flow cytometry techniques enable high-throughput single-cell experiments with extensive marker sets. In order to leverage this technology the measured signal must be unmixed to recover interpretable re- sults. Current approaches to unmixing typically leverage linear deconvolution algorithms such as fitting by ordinary least squares method, that tend have issues dealing with various noise sources inherit to the data collection pro- cess. This thesis evaluates the performance of a novel non-linear approach of unmixing called nougad. For the evaluation, we have generated realistic arti- ficial data with known ground truth for testing, implemented multi-threaded version of nougad and tuned its hyperparameters using Bayesian optimiza- tion, and collected several performance metrics of nougad and the other algorithms on the testing datasets. The results show that nougad is able to outperform the tested linear algorithms making this non-linear method more suitable for practical applications and a good candidate for further refinement and optimization efforts. 1
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