exploreBic {BcDiag} | R Documentation |
Provides exploratory plots for biclustered and clustered data.
exploreBic(dset, bres, gby ="genes", pfor ="mean", mname ="biclust", bnum =1,
fabia.thresZ=0.5,fabia.thresL=NULL)
dset |
data matrix. |
bres |
bicluster result. |
gby |
dimension to plot; 'genes' or 'conditions'. |
pfor |
plot for 'mean', 'median', 'variance', 'mad', 'all', or 'quant' (quantile). |
mname |
method name; 'biclust', 'isa2', 'fabia' or 'bicare' |
bnum |
existing biclusters; '1','2'... |
fabia.thresZ |
Bicluster threshold for |
fabia.thresL |
Bicluster threshold for |
The exploreBic function is mainly used for exploratory data analysis. It provides summary plots for mean, median, variance, MAD and quantile plot.
The exploreBic
function checks if the parameters are appropriately submitted and then identifies the biclusters submatrix and calculates its summary statistics. Finally, the results are displayed on the required plot.
Note that the "biclust"
option for mname
will also accept results from the packages iBBiG and rqubic.
Summary plot will display according to the user specification.
Mengsteab Aregay mycs.zab@gmail.com
Van't Veer, L.J., Dai, H., van de Vijver, M.J., He, Y.D., Hart, A.A. et al. (2002). Gene expression profiling predicts clinical outcome of breast cancer,Nature, 415, 530-536.
Hochreiter, S., Bodenhofer, U., Heusel, M.et al. (2010).FABIA: factor analysis for bicluster acquisition. Bioinformatices, 26, 1520-1527.
data(breastc)
# find bicluster using biclust package
library(biclust)
bic <- biclust(breastc,method=BCPlaid())
# Plot the mean of biclusterd and clustered genes parallely.
exploreBic(dset=breastc,bres=bic,gby="conditions",pfor="mean",mname="biclust")