stat.ma {sma} | R Documentation

## Calculation of log Intensity Ratios and Average log Intensities

### Description

Computes the log intensity ratio M = log_2 (R/G) and the mean log intensity A = log_2(R*G)/2, where R and G represent the fluorescence intensities in the red and green channels, respectively. Logarithms base 2 are used instead of natural or decimal logarithms as intensities are typically integers between 1 and 2^{16}. The log intensity ratios M are normalized using one of the five available methods.

### Usage

    stat.ma(RG, layout, norm="p", pout=FALSE, ...)

### Arguments

`RG` | a list with 4 elements, each represents a matrix with p rows for p genes and n columns for n slides. The first element "R" contains the raw red intensities from slide i=1,...,n . Similarly, the second element "G" contains the raw green intensities. The third element "Rb" contains the background red intensities and the fourth element "Gb" contains the background green intensities. This list structure can be generated by the interactive function `init.data`.
`layout` | a list specifying the dimensions of the spot matrix and the grid matrix. This can be generated by calling `init.grid`.
`norm` | Character string, one of "n", "m", "l", "p" or "s". This argument specifies the type of normalization method to be performed: "n" no normalization between the 2 channels; "m" `median` normalization, which sets the median of log intensity ratios to zero; "l" global `lowess` normalization; "p" print-tip group lowess normalization and "s" scaled print-tip group lowess normalization. The default method is set to print-tip normalization.
`pout` | if TRUE, an M vs. A plot will be produced. Otherwise, a matrix of log intensity ratios and average log intensities is return. By default pout is set to FALSE. The option pout='TURE' is not yet implemented.
`...` | other parameters used in `ma.func`.

### Value

List containing the following components:

`M` | Matrix of log expression ratios M = log_2 (R/G)
`A` | Matrix of average log intensities A = log_2(R*G)/2

For the matrix in each of the components, rows correspond to genes and columns correspond to different hybridizations, that is different slides.

### Note

`ma.func`, `norm.l.func`, `norm.scale.func` and `norm.pin.func` are called by `stat.ma` and are not typically used on their own.

### Author(s)

Yee Hwa Yang, yeehwa@stat.berkeley.edu
Sandrine Dudoit, sandrine@stat.berkeley.edu
Natalie Roberts, nroberts@wehi.edu.au

### References

S. Dudoit, Y. H. Yang, M. J. Callow, and T. P. Speed. Statistical methods for identifying differentially expressed genes in replicated cDNA microarray experiments (Statistics, UC Berkeley, Tech Report # 578).

### See Also

`ma.func`, `norm.l.func`, `norm.pin.func`, `norm.scale.func`, `plot.mva`, `lowess`.

### Examples

    data(MouseArray)
    ## mouse.setup <- init.grid()
    ## mouse.data <- init.data() ## see \emph{init.data}
    mouse.lratio <- stat.ma(mouse.data, mouse.setup)

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