plotFreqStat {aCGH} | R Documentation

## frequency plots and significance analysis

### Description

The main application of this function is to plot the frequency of changes.

### Usage

    plotFreqStat(aCGH.obj, resT = NULL, pheno = rep(1, ncol(aCGH.obj)),
                 chrominfo = human.chrom.info.Jul03,
                 X = TRUE, Y = FALSE,
                 rsp.uniq = unique(pheno),
                 all = length(rsp.uniq) == 1 && is.null(resT),
                 titles = if (all) "All Samples" else rsp.uniq,
                 cutplot = 0, thres = .25, factor = 2.5, ylm = c(-1, 1),
                 p.thres = c(.01, .05, .1), numaut = 22, onepage = TRUE,
                 colored = TRUE)

### Arguments

`aCGH.obj` | Object of class `aCGH`
`resT` | Data frame having the same structure as the result of applying `mt.maxT` or `mt.minP` functions from Bioconductor's `multtest` package for multiple testing. The result is a data frame including the following 4 components: 'index', 'teststat', 'rawp' and 'adjp'.
`pheno` | phenotype to compare.
`chrominfo` | Chromosomal information. Defaults to `human.chrom.info.Jul03`
`X` | Include X chromosome? Defaults to yes.
`Y` | Include Y chromosome? Defaults to no.
`rsp.uniq` | `rsp.uniq` specified the codes for the groups of interest. Default is the unique levels of the phenotype. Not used when `all` is T.
`all` | `all` specifies whether samples should be analyzed by subgroups (T) or together (F).
`titles` | `titles` names of the groups to be used. Default is the unique levels of the `pheno`.
`cutplot` | only clones with at least `cutplot` frequency of gain and loss are plotted.
`thres` | `thres` is either a vector providing unique threshold for each sample or a vector of the same length as number of samples (columns in `data`) providing sample-specific threshold. If `aCGH.obj` has non-null sd.samples, then `thres` is automatically replaced by `factor` times madGenome of `aCGH` object. Clone is considered to be gained if it is above the threshold and lost if it below negative threshold. Used for plotting the gain/loss frequency data as well as for clone screening and for significance analysis when `threshold` is TRUE.Defaults to 0.25
`factor` | `factor` specifies the number by which experimental variability should be multiplied. used only when sd.samples(`aCGH.obj`) is not NULL or when factor is greater than 0. Defaults to 2.5
`ylm` | `ylm` vertical limits for the plot
`p.thres` | `p.thres` vector of p-value ciut-off to be plotted. computed conservatively as the threshold corresponding to a given adjusted p-value.
`numaut` | `numaut` number of the autosomes
`onepage` | `onepage` whether all plots are to be plotted on one page or different pages. When more than 2 groups are compared, we recommend multiple pages.
`colored` | Is plotting in color or not? Default is TRUE.

### Examples

    data(colorectal)

    ## Use mt.maxT function from multtest package to test
    ## differences in group means for each clone grouped by sex
    colnames(phenotype(colorectal))
    sex <- phenotype(colorectal)$sex
    sex.na <- !is.na(sex)
    colorectal.na <- colorectal[ ,sex.na, keep = TRUE ]
    dat <- log2.ratios.imputed(colorectal.na)
    resT.sex <- mt.maxT(dat, sex[sex.na], test = "t", B = 1000)

    ## Plot the result along the genome
    plotFreqStat(colorectal.na, resT.sex, sex[sex.na],
                 titles = c("Male", "Female"))

    ## Adjust the p.values from previous exercise with "fdr"
    ## method and plot them
    resT.sex.fdr <- resT.sex
    resT.sex.fdr$adjp <- p.adjust(resT.sex.fdr$rawp, "fdr")
    plotFreqStat(colorectal.na, resT.sex.fdr, sex[sex.na],
                 titles = c("Male", "Female"))

    ## Derive statistics and p-values for testing the linear association of
    ## age with the log2 ratios of each clone along the samples

    age <- phenotype(colorectal)$age
    age.na <- which(!is.na(age))
    age <- age[age.na]
    colorectal.na <- colorectal[, age.na]
    stat.age <- aCGH.test(colorectal.na, age, test = "linear.regression", p.adjust.method = "fdr")

    #separate into two groups: < 70 and > 70 and plot freqeuncies of gain and loss
    #for each clone. Note that statistic plotted corresponds to linear coefficient
    #for age variable

    plotFreqStat(colorectal.na, stat.age, ifelse(age < 70, 0, 1), titles =
                 c("Young", "Old"), X = FALSE, Y = FALSE)

[Package aCGH version 1.4.1 Index]