The function does a PCA analysis using `prcomp`

function
using percent methylation matrix as an input.

```
PCASamples(.Object, screeplot=FALSE, adj.lim=c(0.0004,0.1), scale=TRUE,
center=TRUE,comp=c(1,2),transpose=TRUE,sd.filter=TRUE,
sd.threshold=0.5,filterByQuantile=TRUE,obj.return=FALSE,chunk.size)
```# S4 method for methylBase
PCASamples(.Object, screeplot, adj.lim, scale, center,
comp, transpose, sd.filter, sd.threshold, filterByQuantile, obj.return)

# S4 method for methylBaseDB
PCASamples(.Object, screeplot = FALSE,
adj.lim = c(4e-04, 0.1), scale = TRUE, center = TRUE, comp = c(1, 2),
transpose = TRUE, sd.filter = TRUE, sd.threshold = 0.5,
filterByQuantile = TRUE, obj.return = FALSE, chunk.size = 1e+06)

.Object

a `methylBase`

or `methylBaseDB`

object

screeplot

a logical value indicating whether to plot the variances against the number of the principal component. (default: FALSE)

adj.lim

a vector indicating the propotional adjustment of xlim (adj.lim[1]) and ylim (adj.lim[2]). This is primarily used for adjusting the visibility of sample labels on the on the PCA plot. (default: c(0.0004,0.1))

scale

logical indicating if `prcomp`

should scale the data to
have unit variance or not (default: TRUE)

center

logical indicating if `prcomp`

should center the data
or not (default: TRUE)

comp

vector of integers with 2 elements specifying which components to be plotted.

transpose

if TRUE (default) percent methylation matrix will be transposed, this is equivalent to doing PCA on variables that are regions/bases. The resulting plot will location of samples in the new coordinate system if FALSE the variables for the matrix will be samples and the resulting plot whill show how each sample (variable) contributes to the principle component.the samples that are highly correlated should have similar contributions to the principal components.

sd.filter

If `TRUE`

, the bases/regions with low variation will
be discarded prior to PCA (default:TRUE)

sd.threshold

A numeric value. If `filterByQuantile`

is `TRUE`

,
the value should be between 0 and 1 and the features whose standard
deviations is less than the quantile denoted by `sd.threshold`

will be removed. If `filterByQuantile`

is `FALSE`

,
then features whose standard deviations is less than the value
of `sd.threshold`

will be removed.(default:0.5)

filterByQuantile

A logical determining if `sd.threshold`

is to be
interpreted as a quantile of all standard deviation values from
bases/regions (the default), or as an absolute value

obj.return

if the result of `prcomp`

function should be returned
or not. (Default:FALSE)

chunk.size

Number of rows to be taken as a chunk for processing the
`methylRawListDB`

objects, default: 1e6

The form of the value returned by `PCASamples`

is the summary
of principal component analysis by `prcomp`

.

The parameter `chunk.size`

is only used when working with
`methylBaseDB`

objects,
as they are read in chunk by chunk to enable processing large-sized
objects which are stored as flat file database.
Per default the chunk.size is set to 1M rows, which should work for most
systems. If you encounter memory problems or
have a high amount of memory available feel free to adjust the
`chunk.size`

.

# NOT RUN { data(methylKit) # do PCA with filtering rows with low variation, filter rows with standard # deviation lower than the 50th percentile of Standard deviation distribution PCASamples(methylBase.obj,screeplot=FALSE, adj.lim=c(0.0004,0.1), scale=TRUE,center=TRUE,comp=c(1,2),transpose=TRUE,sd.filter=TRUE, sd.threshold=0.5,filterByQuantile=TRUE,obj.return=FALSE) # }