SamSPECTRAL

[…] high-dimensional or high-throughput FC data. To address the gating problem, researchers have proposed several automated clustering algorithms, such as FLAME (), FLOCK (), flowClust (), flowMeans (), SamSPECTRAL (), SWIFT (), etc. Aghaeepour et al. () provides a state-of-the-art summary of the field.Different algorithms perform better for different FC datasets as was observed in a set of challenge […]

[…] n surface markers. The staining panel contains antibodies to surface markers and intracellular proteins.Additionally, we compared our method against four well-known algorithms in the field: FLAME [], SamSpectral [], flowMerge [], and flowMeans []. […]

[…] aussian models, t-mixture models and skew-t models []. These methods show robustness that follows predefined models, but they might be slow at estimating model parameters of high-dimensional dataset. SamSPECTRAL [] is an example of the graph-based methods, while multidimensional clustering approaches available include SPADE [], flowMeans [] and FLOCK []. Here, we investigated whether one of the ex […]

[…] -user were used as guidance, the f-scores improved dramatically, with five algorithms ending up with scores of 0.90 or greater. As before, this not only included ADIcyt, FlowMeans, and FLOCK but also SamSpectral () and TCLUST (). The overall conclusion from this challenge was that although some packages performed better than others, most performed well and this was largely dependent on the dataset […]

[…] al clustering approaches have recently been developed, including model-based algorithms (e.g., flowClust and FLAME ), density-based algorithms (e.g., FLOCK and SWIFT), graph-based approaches (e.g., SamSPECTRAL ), and, most recently, hybrids of several approaches (flowMeans and flowPeaks ). These algorithms are different in terms of memory and time complexity, their software requirements, their […]

[…] ectly apply classical spectral clustering [-] to the lymphoma data because it involved computing eigenvectors of a big n-by-n matrix where n ranges from 20,000 to 70,000. Instead, we have made use of SamSPECTRAL that is our enhanced spectral clustering method capable of analyzing large amount of data in a reasonable amount of time; it has also a good memory footprints [].SamSPECTRAL performs a spe […]