CAFE-package {CAFE} | R Documentation |
CAFE attempts to find chromosomal aberrations in microarray expression (mRNA) data. It contains several plotting functions to aid in visualizing these aberrations. It generally recapitulates the workflow described by Mayshar et al (see references), and implements several algorithms described by Friedrich et al (see references).
Package: | CAFE |
Type: | Package |
Version: | 0.6.9.5 |
Date: | 2013-05-16 |
License: | GPLv3 |
Sander Bollen
Friedrich, F., Kempe, a, Liebscher, V., & Winkler, G. (2008). Complexity Penalized M-Estimation. Journal of Computational and Graphical Statistics, 17(1), 201-224. doi:10.1198/106186008X285591
Mayshar, Y., Ben-David, U., Lavon, N., Biancotti, J.-C., Yakir, B., Clark, A. T., Plath, K., et al. (2010). Identification and classification of chromosomal aberrations in human induced pluripotent stem cells. Cell stem cell, 7(4), 521-31. doi:10.1016/j.stem.2010.07.017
## Not run: setwd("/some/path/to/cel/files") data <- ProcessCels() # process cel files samples <- c(1,2) # select samples 1 and 2 to compare against the rest chromosomeStats(data,chromNum="ALL",samples=samples) # check for chromosomal gains chromosomeStats(data,chromNum="ALL",samples=samples,alternative="less") # check for chromosomal losses bandStats(data,chromNum=1,samples=samples) # check for band gains in chr1 bandStats(data,chromNum=1,samples=samples,alternative="less") # check for band losses in chr1 rawPlot(data,chromNum=1,samples=samples,idiogram=TRUE) # plot raw data with an ideogram slidPlot(data,chromNum=1,samples=samples,idiogram=TRUE,combine=TRUE,k=100) # moving average plot with ideogram discontPlot(data,chromNum=1,samples=samples,idiogram=TRUE) # discontinuous plot with ideogram ## End(Not run)