kernlab, cclust, dbscan, kohonen, MCL, ADPclust, cluster,
DatabionicSwarm, orclus, subspace, flexclust, ABCanalysis,
apcluster, pracma,EMCluster, pdfCluster, parallelDist, plotly,
ProjectionBasedClustering, GeneralizedUmatrix, mstknnclust,
densityClust, parallel, energy, R.utils, tclust, Spectrum,
genie, protoclust, fastcluster, clusterability, signal,
reshape2, PPCI, clustrd, smacof, rgl,prclust, dendextend,
moments,prabclus, VarSelLCM, sparcl, mixtools, HDclassif,
clustvarsel, yardstick, knitr, rmarkdown, igraph, leiden,
clusterSim, NetworkToolbox

A Collection of Fluorescence Fluctuation Spectroscopy Methods
A set of tools for fluorescence fluctuation spectroscopy data analysis performance is provided in this package.
It includes techniques such as single-point fluorescence correlation spectroscopy, autocorrelation and pair correlation functions, number & brightness (raster line scan) and a novel method recently developed by Hinde and co-workers, pair correlation of molecular brightness.
A set of simulations and real experimental data is used for the examples of each function provided in this package.
For an in-depth description of the basics behind each function here included and a detailed step-by-step guide on how to use them on your own data, please refer to the Supplementary Material file provided at (<https://github.com/RPintoC/FCSlib_Sup>).
R.A. Migueles-Ramirez, A.G. Velasco-Felix, R. Pinto-Camara, C.D. Wood, A. Guerrero (2017, ISBN-13:978-84-942134-9-6).
Hinde, E., Pandzic, E., Yang, Z., Ng, I. H., Jans, D. A., Bogoyevitch, M. A., Gratton, E. & Gaus, K. (2016) <doi:10.1038/ncomms11047>.

A set of tools for fluorescence fluctuation spectroscopy data analysis performance is provided in this package.
It includes techniques such as single-point fluorescence correlation spectroscopy, autocorrelation and pair correlation functions, number & brightness (raster line scan) and a novel, recently developed method by Hinde and co-workers, pair correlation of molecular brightness (doi:10.1038/ncomms11047).
A set of simulations and real experimental data is used for the examples of each function provided in this package.
For an in-depth description of the basics behind each function here included and a detailed step-by-step guide on how to use them on your own data, please refer to the Supplementary Material file provided at (<https://github.com/RPintoC/FCSlib_Sup_Data>).