fitWithin {stepNorm} | R Documentation |

This function performs location normalization on cDNA
micoroarray. It operates on class `marrayRaw`

or class `marrayNorm`

. It allows the user to choose from a set of three basic normalization procedures.

fitWithin(x.fun = "maA", y.fun = "maM", z.fun = TRUE, subset=TRUE, fun = "medfit", ...)

`x.fun` |
Name of accessor method for spot intensity, usually `maA` . |

`y.fun` |
Name of accessor method for spot statistics, usually the log-ratio `maM` . |

`z.fun` |
Name of accessor method for spot statistic used to
stratify the data, usually a layout parameter,
e.g. `maPrintTip` or
`maCompPlate` . If `z` is not a
character, e.g. NULL, the data are not stratified. |

`subset` |
A "logical" or "numeric" vector indicating the subset of points used to compute the normalization values. |

`fun` |
Character string specifying the normalization procedure: |

`...` |
Miscs arguments to be passed in `fun` |

Normalization is typically performed on the expression ratios of cDNA
microarray data, using the function specified by argument
`fun`

. Currently, this function is to be chosen from:
`medfit`

(median), `rlmfit`

(rlm) and
`loessfit`

(loess). When `z.fun`

is provided as a character
string, for example, `maPrintTip`

, the normalization procedure is
operated within each print-tip of the slide.

The function `fitWithin`

returns a function(*F*) with
bindings for `x.fun`

, `y.fun`

, `z.fun`

, `subset`

and `fun`

. When the function *F* is evaluated with an object
of class `marrayNorm`

or
`marrayRaw`

, it carries out normalization
and returns an object of class `marrayFit`

that contains
the normalization information as a list with the following
list components:

`varfun` |
: A character vector of names of predictor variables. |

`x` |
: A numeric matrix of predictor variables. |

`y` |
: A numeric matrix of repsonses. |

`residuals` |
: A numeric matrix of normalized values (typically
log ratios (M)). |

`fitted` |
: A numeric matrix of the fitted values. |

`enp` |
: The equivalent number of parameters; see `loess` . |

`df.residual` |
: The residual degrees of freedom. |

`fun` |
: A character string indicating the name of the function used for normalization. |

Note that the `residuals`

component stores the normalized ratios.

Yuanyuan Xiao, yxiao@itsa.ucsf.edu,

Jean Yee Hwa Yang, jean@biostat.ucsf.edu

Y. H. Yang, S. Dudoit, P. Luu, and T. P. Speed (2001). Normalization
for cDNA microarray data. In M. L. Bittner, Y. Chen, A. N. Dorsel, and
E. R. Dougherty (eds), *Microarrays: Optical Technologies and
Informatics*, Vol. 4266 of *Proceedings of SPIE*.

## using the swirl data as example data(swirl) ## median normalization med <- fitWithin(fun="medfit") swirl1.med <- med(swirl[,1]) norm.M <- swirl1.med$residuals ## matrix of normalized ratios ## rlm normalization rlmF <- fitWithin(fun="rlmfit") swirl1.rlm <- rlmF(swirl[,1]) ## loess normalization, default span=0.4 loessF <- fitWithin(fun="loessfit") swirl1.loess <- loessF(swirl[,1]) ## loess normalization, span=0.2 loessF.1 <- fitWithin(fun="loessfit", span=0.2) swirl1.loess.1 <- loessF.1(swirl[,1]) ## within-printtip loess normalization loessP <- fitWithin(z.fun="maPrintTip", fun="loessfit") swirl1.loessP <- loessP(swirl[,1])

[Package *stepNorm* version 1.0.2 Index]