MMClustering1.0
Normal, t, Skew-normal, and skew-t Mixture-Model Clustering.
Ali OghabianClusteringFlowCytometryR, RmpiLocation of the csv files to be clustered e.g. Preprocessed files in
flow cytometry analysis .The minimum number of the Mixture Model clusters.It is considering that
results for some clusters might be Null. As for instance, the results for
MMclustering with g parameter (i.e. expected cluster number) of 5 might group the
rows of the data in 4 clusters of 1,2,4,and 5.The maximum number of the "Mixture Model" clusters. It is considering that
results for some clusters might be Null. As for instance, the results for
MMclustering with g parameter (i.e. expected cluster number) of 5 might group the
rows of the data in 4 clusters of 1,2,4,and 5.Density distribution to be used for clustering: normal, t, skew
normal, skew t.A comma-separated list of column names or column numbers (e.g. channel names/
numbers in flow cytometry analysis), to be clustered. As for instance the value
could be set as "1, 2, 3, 4, 5" or "FSC.A, SSC, ERK1, STAT1, CD4" . The column representing the row numbers. The parameter is optional and it would be added to the
"postProb" files, if provided. A comma-separated list of column names or column numbers (e.g. channel names/
numbers in flow cytometry analysis), to be plotted. As for instance the value
could be set as "1, 2, 3, 4, 5" or "FSC.A, SSC, ERK1, STAT1, CD4". This parameter is only for the "regular2d" and "regullar3d" plottings.Whether remove the rows with na from the data or return an Error.The seed value for semi-random processesUsed only for skew distributions. Whether to estimate the mode
for each cluster. The defalt value (i.e. false) is recommendedOnly used when Density is "skew" and the estimateMode is "true".
It is used to calculated the number of the iterations of the
Expected-Maximization (i.e. EM), while computing the Maximum
Likelihood (i.e ML) estimate. The value should be greater than 0.
The smaller the value, the more accurate the estimations would be.Tells if the result document should start with a page break.The maximum limitation for the number of iterations, in the mixturemodeling fitting process A value used for threshold in the mixture modeling fitting process. The
smaller the value the more accurate the cluster results are. If the clusters do
not satisfy the epsilon threshold in iterationMaximum iteration attempts an
error would be returned. The number of the clusters used for paralelising the Mixture
Modeling.Whether write the Mixture Model parameters.Whether include the plotting images in the report directory.The type and shape of plotting points. Numbers (e.g. "2") and characters (e.g. ".") are possible. The type of Plotting. The choices are regular2d, regular3d,
contour2d, individualcontour2d, and boundry2d.Whether include the Posterior probabilities. Check "the postProb" output for more information. The name of the column in the clusters output
which contains the cluster IDs of the rows.