plotChr: Plot Smoothed Sense/Anti-sense of Specified Chromosomes
In geneplotter: Graphics related functions for Bioconductor

Description Usage Arguments Author(s) See Also Examples

For a given chromosome, plot the smooths of the sense and the anti-sense from 5' to 3' (left to right on x-axis).

1	plotChr(chrN, senseObj, cols = rep("black", length(senseObj[[1]])), log = FALSE, xloc = c("equispaced", "physical"), geneSymbols = FALSE, ngenes = 20, lines.at = NULL, lines.col = "red")

`chrN`	The desired chromosome, e.g. for humans it would be a character string in the set of c(1:22, "X", "Y").
`senseObj`	The result of `Makesense`.
`cols`	A vector of colors for the lines in the plot, typically specified according to a certain pheotype of samples.
`log`	Logical, whether log-transformation should be taken on the smoothed expressions.
`xloc`	Determines whether the "Representative Genes" will be displayed according to their relative positions on the chromosome (physical), or spaced evenly (equispaced). Default is equispaced.
`geneSymbols`	Logical, whether to use Affy IDs or Gene Symbols for "Representative Genes", default is Affy IDs.
`ngenes`	Desired number of "Representative Genes". The number of actual displayed genes may differ.
`lines.at`	A vector of Affy IDs. Vertical lines will be drawn at specified genes.
`lines.col`	A vector of colors associated with `lines.at`.

Robert Gentleman and Xiaochun Li

Makesense

example(Makesense)

if (interactive())
  op <- par(ask=TRUE)

cols <- ifelse(expressionSet133a$cov1=="test 1", "red", "green")
plotChr("21", esetobj, cols)

# plot on log-scale:

plotChr("21", esetobj, cols, log=TRUE)

# genesymbol instead of probe names:

plotChr("21", esetobj, cols, log=TRUE, geneSymbols=TRUE)

# add vertical lines at genes of interest:

gs <- c("220372_at", "35776_at", "200943_at")
plotChr("21", esetobj, cols, log=TRUE, geneSymbols=FALSE, lines.at=gs)

# add vertical lines at genes of interest
# with specified colors:

gs <- c("220372_at", "35776_at", "200943_at")
cc <- c("blue", "cyan","magenta")
plotChr("21", esetobj, cols, log=TRUE, geneSymbols=FALSE, lines.at=gs,
lines.col=cc)
if (interactive())
  par(op)

Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, basename, cbind, colMeans, colSums, colnames,
    dirname, do.call, duplicated, eval, evalq, get, grep, grepl,
    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: lattice
Loading required package: annotate
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:base':

    expand.grid

Loading required package: XML

Maksns>   if (require("hgu133a.db")) {
Maksns+     data(expressionSet133a)
Maksns+     esetobj <- Makesense(exprs(expressionSet133a), "hgu133a")
Maksns+     esetobj2 <- Makesense(expressionSet133a[1:200, ])
Maksns+   }
Loading required package: hgu133a.db
Loading required package: org.Hs.eg.db


Warning messages:
1: In log(-smooths$neg$y) : NaNs produced
2: In log(-smooths$neg$y) : NaNs produced
3: In log(-smooths$neg$y) : NaNs produced
4: In log(-smooths$neg$y) : NaNs produced
5: In log(smooths$pos$y) : NaNs produced
Warning messages:
1: In log(-smooths$neg$y) : NaNs produced
2: In log(-smooths$neg$y) : NaNs produced
3: In log(-smooths$neg$y) : NaNs produced
4: In log(-smooths$neg$y) : NaNs produced
5: In log(smooths$pos$y) : NaNs produced
Warning messages:
1: In log(-smooths$neg$y) : NaNs produced
2: In log(-smooths$neg$y) : NaNs produced
3: In log(-smooths$neg$y) : NaNs produced
4: In log(-smooths$neg$y) : NaNs produced
5: In log(smooths$pos$y) : NaNs produced
Warning messages:
1: In log(-smooths$neg$y) : NaNs produced
2: In log(-smooths$neg$y) : NaNs produced
3: In log(-smooths$neg$y) : NaNs produced
4: In log(-smooths$neg$y) : NaNs produced
5: In log(smooths$pos$y) : NaNs produced