plotHMBayes {iClusterPlus} | R Documentation |
A function to generate heatmap panels sorted by integrated cluster assignment.
plotHMBayes(fit, datasets, type = c("gaussian", "binomial", "poisson"), sample.order = NULL, row.order = NULL, sparse = NULL, threshold = rep(0.5,length(datasets)), width = 5, scale = rep("none",length(datasets)), col.scheme = rep(list(bluered(256)),length(datasets)),chr=NULL, plot.chr=NULL, cap=NULL)
fit |
A iClusterBayes object. |
datasets |
A list object of data matrices. |
type |
Types of data in the datasets. |
sample.order |
User supplied cluster assignment. |
row.order |
A vector of logical values each specify whether the genomic features in the corresponding data matrix should be reordered by similarity. Default is TRUE. |
sparse |
A vector of logical values each specify whether to plot the top cluster-discriminant features. Default is FALSE. |
threshold |
When sparse is TRUE, a vector of threshold values to include the genomic features on the heatmap. Each data set should have a threshold. For each data set, a feature with posterior probability greater than the threshold will be included. Default value is 0.5 for each data set. |
width |
Width of the figure in inches |
scale |
A vector of logical values each specify whether data should be scaled. Default is FALSE. |
col.scheme |
Color scheme. Can use bluered(n) in gplots R package. |
chr |
A vector of chromosome number. |
plot.chr |
A vector of logical values each specify whether to annotate chromosome number on the left of the panel. Typically used for copy number data type. Default is FALSE. |
cap |
Image color option |
The samples are ordered by the cluster assignment by the R code: order(fit$clusters). For each data set, the features are ordered by hierarchical clustering of the features using the complete method and 1-correlation coefficient as the distance.
no value returned.
Ronglai Shen shenr@mskcc.org,Qianxing Mo qmo@bcm.edu
Mo Q, Shen R, Guo C, Vannucci M, Chan KS, Hilsenbeck SG. (2018). A fully Bayesian latent variable model for integrative clustering analysis of multi-type omics data. Biostatistics 19(1):71-86.
# see iManual.pdf