massi-package {massiR} | R Documentation

## massiR: a microarry Gene Expression Sample Sex Identifier

### Description

massi uses y chromosome probe information to cluster samples and predict the sex of each sample in gene expression microarray datasets.

### Details

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.

### Author(s)

Sam Buckberry

Maintainer: Sam Buckberry <sam.buckberry@adelaide.edu.au>

### References

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

### See Also

`massi_y, massi_select, massi_cluster, massi_y_plot, massi_dip, massi_cluster_plot`

### Examples

    # 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]])

[Package massiR version 1.18.0 Index]