A list of data.frames, matrix or ExpressionSet is going to be analyzed,
the column number must be the same and mapped across all data.frame/matrix
cia.nf
An integer indicating the number of kept axes
cia.scan
A logical indicating whether the co-inertia analysis
eigenvalue (scree) plot should be shown so that the number of axes,
(cia.nf) can be selected interactively. Default value is FALSE.
nsc
A logical indicating whether multiple co-inertia analysis should be
performed using multiple non-symmetric correspondence analyses
dudi.nsc. The default =TRUE is highly
recommended. If FALSE, COA dudi.coa
will be performed on the first data.frame, and row weighted
COA dudi.rwcoa will be performed on
the rest ones using the row weights from the first one.
svd
A logical indicates which function should be used to perform singular value decomposition.
sample.lab
A logical indicating if the samples should be labelled, the default is
TRUE.
sample.color
Defining colours of samples for plotting sample space, the length of this
argument should be either one (uniform color) or the same with the
column number of data.frame in df.list.
sample.legend
A logical indicating if the legend for sample space should be drawn.
df.color
Defining the colours for plotting variables (genes) from different data.frame.
The length of this argument should be either one (all datasets use the same
colour) or the same number of datasets (each dataset has a specified colour, the
repetitive use of colour code is allowed.)
df.pch
Defining the pch for plotting variable (gene) space. The default is NA, the function
will distinguish datasets by default. Otherwise, the length of this argument
should be either one (all datasets use the same pch) or the same number
of datasets (each dataset has a specified pch).
phenovec
A factor for plotting sample space, phenovec could be
used to distinguish individuals in the data.frames.
x
An object of class mcia
axes
A vector of integer in length 2 to indicate the axes are going to be plotted.
The default are first two axes.
gene.nlab
An integer indicating how many top weighted genes on each axis should be labelled
...
Other arguments
Details
The column number of data.frame in the df.list must be the same,
and the same column
from different data.frame should be matchable. For example, Microarray
profiling for the same set of cell lines, patients and etc.
mcia calls dudi.nsc,
ktab and mcoa in ade4
packages.
Plotting and visualizing mcia results
Two functions could be used to visualize the result of mcia:
The first is plot.mcia,
which results in four plots. Top left represents the sample space. Individuals
from the same column of different data.frames are linked by edges.
Different platforms are distinguished by the shape of points.
Top right shows the variable space, datasets are marked by different colours.
Bottom left represents the eigenvalue scree plot.
The pseudo-eigenvalue space of all data.frames are visualized in the bottom right panel.
The second function is plotVar.mcia, which could be used to
plot the variable space for different datasets as well as finding and visualizing the
variables (genes) across datasets.
Other methods
selectVar.mcia: selecting variables (genes) according to the their coordinates.
Value
call
the function called
mcoa
The results returned by mcoa
coa
The results returned by separate analysis (applying dudi.nsc
or dudi.coa on each data.frame separately)
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)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(omicade4)
Loading required package: ade4
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/omicade4/mcia.Rd_%03d_medium.png", width=480, height=480)
> ### Name: mcia
> ### Title: multiple co-inertia analysis
> ### Aliases: mcia plot.mcia
> ### Keywords: mcia
>
> ### ** Examples
>
>
> data(NCI60_4arrays)
> mcoin <- mcia(NCI60_4arrays)
> plot(mcoin, sample.lab=FALSE, df.col=4:7)
>
> colcode <- sapply(strsplit(colnames(NCI60_4arrays$agilent), split="\."),
+ function(x) x[1])
> plot(mcoin, sample.lab=FALSE, sample.color=as.factor(colcode))
>
>
>
>
>
>
> dev.off()
null device
1
>