PCASamples {methylKit} | R Documentation

## Principal Components Analysis of Methylation data

### Description

The function does a PCA analysis using `prcomp` function using percent methylation matrix as an input.

### Usage

    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 signature 'methylBase'
    PCASamples(.Object, screeplot, adj.lim, scale, center,
      comp, transpose, sd.filter, sd.threshold, filterByQuantile, obj.return)

    ## S4 method for signature '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)

### Arguments

`.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

### Value

The form of the value returned by `PCASamples` is the summary of principal component analysis by `prcomp`.

### Details

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`.

### Note

cor option is not in use anymore, since `prcomp` is used for PCA analysis instead of `princomp`

### Examples

    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)

[Package methylKit version 1.6.3 Index]