Description: Provides utilities for clustering subjects and variables of mixed data types (Hummel, Edelmann, Kopp-Schneider (2017) <doi: 10.1371/journal.pone.0188274>). Similarities between subjects are measured by Gower's general similarity coefficient with an extension of Podani for ordinal variables. Similarities between variables can be assessed i) by combination of appropriate measures of association for different pairs of data types or ii) based on distance correlation. Alternatively, variables can also be clustered by the 'ClustOfVar' approach. The main feature of the package is the generation of a mixed-data heatmap. For visualizing similarities between either subjects or variables, a heatmap of the corresponding distance matrix can be drawn. Associations between variables can be explored by a 'confounder plot', which allows visual detection of possible confounding, collinear, or surrogate factors for some variables of primary interest. Distance matrices and dendrograms for subjects and variables can be derived and used for further visualizations and applications. This work was supported by BMBF grant 01ZX1609B, Germany.

Description: CLUE is an R package for identifying optimal number of clusters in a given time-course dataset clustered by cmeans or kmeans algorithms.

Description: CLUster Evaluation (CLUE) is a computational method for identifying optimal number of clusters in a given time-course dataset clustered by cmeans or kmeans algorithms and subsequently identify key kinases or pathways from each cluster. Its implementation in R is called ClueR. See Readme on <https://github.com/PengyiYang/ClueR> for more details.

Description: CLUster Evaluation (CLUE) is a computational method for identifying
optimal number of clusters in a given time-course dataset clustered by
cmeans or kmeans algorithms and subsequently identify key kinases or
pathways from each cluster. Its implementation in R is called ClueR.
See README on <https://github.com/PengyiYang/ClueR> for more details.
Packaged: 2018-06-10 13:32:46 UTC; pengyiyang