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

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]])

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

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Type 'demo()' for some demos, 'help()' for on-line help, or
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Type 'q()' to quit R.

> library(massiR)
Loading required package: cluster
Loading required package: gplots

Attaching package: 'gplots'

The following object is masked from 'package:stats':

    lowess

Loading required package: diptest
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/massiR/massiR-package.Rd_%03d_medium.png", width=480, height=480)
> ### Name: massi-package
> ### Title: massiR: a microarry Gene Expression Sample Sex Identifier
> ### Aliases: massi-package massi
> 
> ### ** 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)
Error in dev.new() : no suitable unused file name for pdf()
Calls: massi_y_plot -> dev.new
Execution halted