# pairs.DEDS: Pairs Plot for DEDS Objects In Bioconductor-mirror/DEDS: Differential Expression via Distance Summary for Microarray Data

## Description

The function `pairs-DEDS` produces pairs plots of statistics or p values for `DEDS-class` objects.

## Usage

 ```1 2 3 4 5 6 7 8``` ```## S3 method for class 'DEDS' pairs(x, subset=c(1:nrow(x\$stats)), labels = colnames(x\$stats[,-1]), logit = FALSE, diagonal = c("qqnorm", "boxplot", "density", "histogram", "none"), lower = c("cor", "none"), groups.by.deds = TRUE, thresh = 0.05, reg.line = NULL, smooth = FALSE, line.by.group = FALSE, diag.by.group = TRUE, lower.by.group = FALSE, col = palette(), pch = 1:n.groups, lwd = 1, legend.plot = length(levels(groups)) > 1, ...) ```

## Arguments

`x`

An object of `DEDS`.

`subset`

A numeric vector indicating the subset of points to be plotted.

`labels`

A character vector specifying the names of the variables.

`logit`

A logical variable, if `TRUE` the variables are logged, useful when plotting p values.

`diagonal`

A character string specifying the type of plot to be applied in the diagonal panels.

 `diagonal="qqnorm"`: `qqnorm` on the diagonal `diagonal="boxplot"`: `boxplot` on the diagonal `diagonal="density"`: `density` on the diagonal `diagonal="histogram"`: `hist` on the diagonal `diagonal="none"`: no special plot will be applied on the diagonal
`lower`

A character string specifying the function to be applied in the lower panels.

 `lower="cor"`: absolute correlation will be put on the lower panel `none="cor"`; no special function will be applied
`groups.by.deds`

A logcial variable, if `TRUE`, points will be separated into groups according to their magnitude of q- or p-values by DEDS.

`thresh`

A numeric variable, if `thresh`<1, it specifies the threshold of significance in differential expression (DE) for q- or p-values of the DEDS object; default is set at 0.05. If `thresh`>1, it specifies the number of top DE genes to be highlighted.

`reg.line`

A function name specifying the type of regression line to be plotted in the scatter plots. If `reg.line=lm`, linear regression line will be plotted; If `reg.line=NULL`, no regression line will be plotted in the scatter plot.

`smooth`

A logical variable specifying if smooth regression lines will be plotted in the scatter plots. If `smooth=TRUE`, a `lowess` line will be applied.

`line.by.group`

A logical variable specifying if the regression lines should be applied within groups.

`diag.by.group`

A logical variable specifying if the plot in the diagonal panels would be applied groupwise.

`lower.by.group`

A logical variable, if `lower.by.group=TRUE` and `lower="cor"`, correlation coefficients will be calculated and printed separated according to groups in the lower panels.

`col`

A specification for the colors to be used for plotting different groups, see `par`.

`pch`

A specification for the type of points to be used for plotting different groups, see `par`.

`lwd`

A specification for the width of lines to be used if lines are plotted; see `par`.

`legend.plot`

A logical variable specifying if the legend will be plotted.

`...`

Extra parameters for plotting.

## Details

The function `pairs.DEDS` implements a S3 method of `pairs` for `DEDS`. The `DEDS` class is a simple list-based class to store DEDS results and it is usually created by functions `deds.pval`, `deds.stat`, `deds.stat.linkC`. The list contains a "stat" component, which stores statistics or p values from various statistical tests. The function `pairs.DEDS` extracts the "stat" component and produces a matrix of scatterplot.

`pairs.DEDS` as a default highlights points (corresponding to genes) with adjusted p- or q-values less than a user defined threshold. The user can select among a series of options a plot for the diagonal panel; as a default, it produces a `qqnorm` for each column in the "stat" matrix. Both the diagonal and lower panels can be stratified by specifying the `diag.by.group` or `lower.by.group` arguments.

## Author(s)

Yuanyuan Xiao, [email protected],
Jean Yee Hwa Yang, [email protected].

`deds.stat`, `deds.pval`, `deds.stat.linkC`, `hist.DEDS`, `qqnorm.DEDS`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```X <- matrix(rnorm(1000,0,0.5), nc=10) L <- rep(0:1,c(5,5)) # genes 1-10 are differentially expressed X[1:10,6:10]<-X[1:10,6:10]+1 # DEDS d <- deds.stat.linkC(X, L, B=200) # pairs plot pairs(d) # plot regression line pairs(d, reg.line=lm, lwd=2) # histogram in the diagonal panel pairs(d, diagonal="hist") # boxplot on the diagonal panel and stratified pairs(d, diagonal="boxplot", diag.by.group=TRUE) ```