Description Details Author(s) References See Also Examples
massi uses y chromosome probe information to cluster samples and predict the sex of each sample in gene expression microarray datasets.
Package: | massi |
Type: | Package |
Version: | 0.99.0 |
Date: | 2014-01-27 |
License: | GPL-3 |
The massi analysis requires a typical normalized sample/probe values produced by a microarray experiment. The massi_y
function will extract the y chromosome probe information and caculate y chromosome probe variance to allow the used to select the most informative probes. Using the massi_select
function the used can select a probe variation threshold to reduce the number of probes used in the massi.cluster step. The massi_cluster
function clusters samples into two clusters using the y chromosome probe values. Clustering is performed using the K-medoids method as implimented in the "fpc" package. There are two plotting fucntions, massi_y_plot
and massi_cluster_plot
, that allow the user to explore the data at various stages of the analysis. There is also a function, massi_dip
, that can be used to test if there may be a sample sex-bias in the dataset.
Sam Buckberry
Maintainer: Sam Buckberry <sam.buckberry@adelaide.edu.au>
Christian Hennig (2013). fpc: Flexible procedures for clustering. R package version 2.1-6. http://CRAN.R-project.org/package=fpc
Martin Maechler (2013). diptest: Hartigan's dip test statistic for unimodality - corrected code. R package version 0.75-5. http://CRAN.R-project.org/package=diptest
Gregory R. Warnes, Ben Bolker, Lodewijk Bonebakker, Robert Gentleman, Wolfgang Huber Andy Liaw, Thomas Lumley, Martin Maechler, Arni Magnusson, Steffen Moeller, Marc Schwartz and Bill Venables (2013). gplots: Various R programming tools for plotting data. R package version 2.12.1. http://CRAN.R-project.org/package=gplots
massi_y, massi_select, massi_cluster, massi_y_plot, massi_dip, massi_cluster_plot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | # load the test datasets
data(massi.test.dataset, massi.test.probes)
# use the massi.y function to calculate probe variation
massi_y_out <- massi_y(expression_data=massi.test.dataset, y_probes=massi.test.probes)
# plot probe variation to aid in deciding on the most informative subset of y chromosome probes
massi_y_plot(massi_y_out)
# Extract the informative probes for clustering
massi_select_out <- massi_select(massi.test.dataset, massi.test.probes, threshold=4)
# cluster samples to predict the sex for each sample
massi_cluster_out <- massi_cluster(massi_select_out)
# get the predicted sex for each sample
data.frame(massi_cluster_out[[2]])
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