Nothing
R/smooth.region.plot.R
In MVisAGe: Compute and Visualize Bivariate Associations
Defines functions
smooth.region.plot
Documented in
smooth.region.plot
#' A Function for Plotting Smoothed Pearson Correlation Coefficients Genomewide
#'
#' This function plots smoothed R or R^2 values produced by corr.list.compute() genomewide.
#'
#' @param plot.list A list produced by corr.list.compute().
#'
#' @param plot.chr The chromosome for which gene-level R or R^2 values will be plotted.
#'
#' @param plot.start The genomic position (in base pairs) where the plot will start.
#'
#' @param plot.stop The genomic position (in base pairs) where the plot will stop.
#'
#' @param plot.column "R" or "R^2" depending on whether Pearson correlation coefficients or squared Pearson
#' correlation coefficients will be plotted. Default = "R^2".
#'
#' @param annot.colors A vector of colors used for plotting values in different entries of plot.list. Default = c("black", "red", "green", "blue", "cyan").
#'
#' @param vert.pad Amount of vertical white space in the plot. Default = 0.
#'
#' @param ylim.low Smallest value on the y-axis (used to control the range of values on the y-axis). Default = NULL.
#'
#' @param ylim.high Largest value on the y-axis (used to control the range of values on the y-axis). Default = NULL.
#'
#' @param lty.vec Vector specifying line types for plotting values in different entries of plot.list. Default = NULL. See \code{\link{par}}.
#'
#' @param lwd.vec Vector specifying line widths for plotting values in different entries of plot.list. Default = NULL. See \code{\link{par}}.
#'
#' @param plot.legend Logical value specifying whether a legend should be included. Default = FALSE.
#'
#' @param legend.loc Character value specifing the location of the legend. Default = "topright". See See \code{\link{legend}}.
#'
#' @param loess.span A numerical value used to control the level of smoothing. Smoothing is performed separately for each chromosome,
#' and loess.span effectively defines the number of genes in each smoothing window. Default = 250.
#'
#' @param expand.size A numerical value used to control smoothing at the ends of the region of interest. Both ends of the region are artificially
#' extended by expand.size genes, smoothing is performed on the expanded region, and then the smoothed values are restricted to the size
#' of the original region. Default = 50.
#'
#' @param xaxis.label Text used to label the x-axis of the plot. Default = "Chromosome". See \code{\link{plot}}.
#'
#' @param yaxis.label Text used to label the y-axis of the plot. Default = NULL. See \code{\link{plot}}.
#'
#' @param main.label Text used to label the plot header. Default = NULL. See \code{\link{plot}}.
#'
#' @param axis.cex Numerical value used to specify the font size on the axes. Default = 1. See \code{\link{par}}.
#'
#' @param label.cex Numerical value used to specify the font size for the axis labels. Default = 1. See \code{\link{par}}.
#'
#' @param xaxis.line Numerical value used to specify location of xaxis.label. Default = 0. See \code{\link{mtext}}.
#'
#' @param yaxis.line Numerical value used to specify location of yaxis.label. Default = 0. See \code{\link{mtext}}.
#'
#' @param main.line Numerical value used to specify location of main.label. Default = 0. See \code{\link{mtext}}.
#'
#' @return Creates a plot of gene-level R or R^2 values produced by corr.list.compute().
#'
#' @examples exp.mat = tcga.exp.convert(exp.mat)
#'
#' cn.mat = tcga.cn.convert(cn.mat)
#'
#' prepped.data = data.prep(exp.mat, cn.mat, gene.annot, sample.annot, log.exp = FALSE)
#'
#' pd.exp = prepped.data[["exp"]]
#'
#' pd.cn = prepped.data[["cn"]]
#'
#' pd.ga = prepped.data[["gene.annot"]]
#'
#' pd.sa = prepped.data[["sample.annot"]]
#'
#' output.list = corr.list.compute(pd.exp, pd.cn, pd.ga, pd.sa)
#'
#' smooth.region.plot(plot.list = output.list, plot.chr = 11, plot.start = 0e6, plot.stop = 135e6)
#'
#' @export
smooth.region.plot = function(
plot.list,
plot.chr,
plot.start,
plot.stop,
plot.column = "R^2",
annot.colors = c("black", "red", "green", "blue", "cyan"),
vert.pad = 0.05,
ylim.low = NULL,
ylim.high = NULL,
plot.legend = TRUE,
legend.loc = "topleft",
lty.vec = NULL,
lwd.vec = NULL,
loess.span = 50,
expand.size = 50,
xaxis.label = "Position (Mb)",
yaxis.label = NULL,
main.label = NULL,
axis.cex = 1,
label.cex = 1,
xaxis.line = 1.5,
yaxis.line = 2.5,
main.line = 0
)
{
#Restrict plot.list to a common set of genes. This may be necessary if
#plot.list has length greater than 1.
common.list.genes = names(which(table(unlist(lapply(plot.list, rownames))) == length(plot.list)))
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][common.list.genes,]
}
#Order entries in plot.list by genomic position
chr = as.numeric(plot.list[[1]][,"chr"])
pos = as.numeric(plot.list[[1]][,"pos"])
chr.pos.perm = order(chr, pos)
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][chr.pos.perm,]
}
#Restrict corr.output.list to a specific genomic window
chr.ind = as.numeric(as.numeric(plot.list[[1]][,"chr"]) == plot.chr)
start.ind = as.numeric(as.numeric(plot.list[[1]][,"pos"]) >= plot.start)
stop.ind = as.numeric(as.numeric(plot.list[[1]][,"pos"]) <= plot.stop)
plot.rows = which(chr.ind * start.ind * stop.ind == 1)
na.list.rows = c()
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][plot.rows,]
na.list.rows = c(na.list.rows, which(is.na(plot.list[[i]][,plot.column])))
}
na.list.rows = unique(na.list.rows)
if (length(na.list.rows) > 0)
{
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][-na.list.rows,]
}
}
#Define other terms for plotting
m = length(plot.rows)
dists = as.numeric(plot.list[[1]][,"pos"])[c(2:m)] -
as.numeric(plot.list[[1]][,"pos"])[c(1:(m - 1))]
dists = c(0, dists)
cumdists = cumsum(dists)
#Loess smoothing for plotting purposes
x.list = vector("list", length(plot.list))
smoothed.list = vector("list", length(plot.list))
names(x.list) = names(plot.list)
names(smoothed.list) = names(plot.list)
for (i in c(1:length(smoothed.list)))
{
loess.xvals = cumdists
loess.start = min(loess.xvals)
loess.xvals = loess.xvals - loess.start
loess.n = length(loess.xvals)
expand.loess.xvals = c(-loess.xvals[(expand.size + 1):2],
loess.xvals, ((2 * max(loess.xvals)) - loess.xvals[(loess.n - 1):(loess.n - expand.size - 1)]))
loess.yvals = as.numeric(plot.list[[i]][,plot.column])
expand.loess.yvals = c(loess.yvals[(expand.size + 1):2],
loess.yvals, loess.yvals[(loess.n - 1):(loess.n - expand.size - 1)])
temp.loess2 = loess(expand.loess.yvals ~ expand.loess.xvals,
span = loess.span/length(expand.loess.xvals), degree = 1, family = "gaussian")
temp.xvals = (temp.loess2$x[(expand.size + 1):(expand.size + loess.n)] + loess.start)
temp.yvals = temp.loess2$fitted[(expand.size + 1):(expand.size + loess.n)]
x.list[[i]] = (temp.xvals + as.numeric(plot.list[[i]][1, "pos"]))/1e6
smoothed.list[[i]] = temp.yvals
}
x.vals = sort(unlist(x.list))
#Create a vector of y-coordinates, then define the limits on the y-axis
plot.vals = c()
for (i in (1:length(smoothed.list)))
{
plot.vals = c(plot.vals, as.numeric(smoothed.list[[i]]))
}
if (!is.null(ylim.low))
{
ylim.low = min(ylim.low, min(plot.vals)) - vert.pad
} else ylim.low = min(plot.vals) - vert.pad
if (!is.null(ylim.high))
{
ylim.high = max(ylim.high, max(plot.vals)) + vert.pad
} else ylim.high = max(plot.vals) + vert.pad
plot(x.vals,
rep(0, length(x.vals)),
xlim = range(x.vals),
ylim = c(ylim.low, ylim.high),
axes = FALSE,
ylab = "",
xlab = "",
type = "n")
if (is.null(lty.vec))
{
lty.vec = rep(1, length(smoothed.list))
}
if (is.null(lwd.vec))
{
lwd.vec = rep(1, length(smoothed.list))
}
for (i in c(1:length(smoothed.list)))
{
lines(x.list[[i]], smoothed.list[[i]], lwd = lwd.vec[i],
col = annot.colors[i], lty = lty.vec[i])
}
axis(side = 1, cex.axis = axis.cex)
axis(side = 2, cex.axis = axis.cex)
mtext(xaxis.label, side = 1, cex = label.cex, line = xaxis.line)
mtext(yaxis.label, side = 2, cex = label.cex, line = yaxis.line)
mtext(main.label, side = 3, cex = label.cex, line = main.line)
if (plot.legend)
{
legend(legend.loc, lwd = rep(3, length(smoothed.list)),
col = annot.colors[c(1:length(smoothed.list))], names(smoothed.list),
bty = "n", inset = .05, lty = lty.vec)
}
}
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MVisAGe documentation built on May 1, 2019, 8:18 p.m.
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Defines functions smooth.region.plot
Documented in smooth.region.plot
#' A Function for Plotting Smoothed Pearson Correlation Coefficients Genomewide
#'
#' This function plots smoothed R or R^2 values produced by corr.list.compute() genomewide.
#'
#' @param plot.list A list produced by corr.list.compute().
#'
#' @param plot.chr The chromosome for which gene-level R or R^2 values will be plotted.
#'
#' @param plot.start The genomic position (in base pairs) where the plot will start.
#'
#' @param plot.stop The genomic position (in base pairs) where the plot will stop.
#'
#' @param plot.column "R" or "R^2" depending on whether Pearson correlation coefficients or squared Pearson
#' correlation coefficients will be plotted. Default = "R^2".
#'
#' @param annot.colors A vector of colors used for plotting values in different entries of plot.list. Default = c("black", "red", "green", "blue", "cyan").
#'
#' @param vert.pad Amount of vertical white space in the plot. Default = 0.
#'
#' @param ylim.low Smallest value on the y-axis (used to control the range of values on the y-axis). Default = NULL.
#'
#' @param ylim.high Largest value on the y-axis (used to control the range of values on the y-axis). Default = NULL.
#'
#' @param lty.vec Vector specifying line types for plotting values in different entries of plot.list. Default = NULL. See \code{\link{par}}.
#'
#' @param lwd.vec Vector specifying line widths for plotting values in different entries of plot.list. Default = NULL. See \code{\link{par}}.
#'
#' @param plot.legend Logical value specifying whether a legend should be included. Default = FALSE.
#'
#' @param legend.loc Character value specifing the location of the legend. Default = "topright". See See \code{\link{legend}}.
#'
#' @param loess.span A numerical value used to control the level of smoothing. Smoothing is performed separately for each chromosome,
#' and loess.span effectively defines the number of genes in each smoothing window. Default = 250.
#'
#' @param expand.size A numerical value used to control smoothing at the ends of the region of interest. Both ends of the region are artificially
#' extended by expand.size genes, smoothing is performed on the expanded region, and then the smoothed values are restricted to the size
#' of the original region. Default = 50.
#'
#' @param xaxis.label Text used to label the x-axis of the plot. Default = "Chromosome". See \code{\link{plot}}.
#'
#' @param yaxis.label Text used to label the y-axis of the plot. Default = NULL. See \code{\link{plot}}.
#'
#' @param main.label Text used to label the plot header. Default = NULL. See \code{\link{plot}}.
#'
#' @param axis.cex Numerical value used to specify the font size on the axes. Default = 1. See \code{\link{par}}.
#'
#' @param label.cex Numerical value used to specify the font size for the axis labels. Default = 1. See \code{\link{par}}.
#'
#' @param xaxis.line Numerical value used to specify location of xaxis.label. Default = 0. See \code{\link{mtext}}.
#'
#' @param yaxis.line Numerical value used to specify location of yaxis.label. Default = 0. See \code{\link{mtext}}.
#'
#' @param main.line Numerical value used to specify location of main.label. Default = 0. See \code{\link{mtext}}.
#'
#' @return Creates a plot of gene-level R or R^2 values produced by corr.list.compute().
#'
#' @examples exp.mat = tcga.exp.convert(exp.mat)
#'
#' cn.mat = tcga.cn.convert(cn.mat)
#'
#' prepped.data = data.prep(exp.mat, cn.mat, gene.annot, sample.annot, log.exp = FALSE)
#'
#' pd.exp = prepped.data[["exp"]]
#'
#' pd.cn = prepped.data[["cn"]]
#'
#' pd.ga = prepped.data[["gene.annot"]]
#'
#' pd.sa = prepped.data[["sample.annot"]]
#'
#' output.list = corr.list.compute(pd.exp, pd.cn, pd.ga, pd.sa)
#'
#' smooth.region.plot(plot.list = output.list, plot.chr = 11, plot.start = 0e6, plot.stop = 135e6)
#'
#' @export
smooth.region.plot = function(
plot.list,
plot.chr,
plot.start,
plot.stop,
plot.column = "R^2",
annot.colors = c("black", "red", "green", "blue", "cyan"),
vert.pad = 0.05,
ylim.low = NULL,
ylim.high = NULL,
plot.legend = TRUE,
legend.loc = "topleft",
lty.vec = NULL,
lwd.vec = NULL,
loess.span = 50,
expand.size = 50,
xaxis.label = "Position (Mb)",
yaxis.label = NULL,
main.label = NULL,
axis.cex = 1,
label.cex = 1,
xaxis.line = 1.5,
yaxis.line = 2.5,
main.line = 0
)
{
#Restrict plot.list to a common set of genes. This may be necessary if
#plot.list has length greater than 1.
common.list.genes = names(which(table(unlist(lapply(plot.list, rownames))) == length(plot.list)))
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][common.list.genes,]
}
#Order entries in plot.list by genomic position
chr = as.numeric(plot.list[[1]][,"chr"])
pos = as.numeric(plot.list[[1]][,"pos"])
chr.pos.perm = order(chr, pos)
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][chr.pos.perm,]
}
#Restrict corr.output.list to a specific genomic window
chr.ind = as.numeric(as.numeric(plot.list[[1]][,"chr"]) == plot.chr)
start.ind = as.numeric(as.numeric(plot.list[[1]][,"pos"]) >= plot.start)
stop.ind = as.numeric(as.numeric(plot.list[[1]][,"pos"]) <= plot.stop)
plot.rows = which(chr.ind * start.ind * stop.ind == 1)
na.list.rows = c()
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][plot.rows,]
na.list.rows = c(na.list.rows, which(is.na(plot.list[[i]][,plot.column])))
}
na.list.rows = unique(na.list.rows)
if (length(na.list.rows) > 0)
{
for (i in (1:length(plot.list)))
{
plot.list[[i]] = plot.list[[i]][-na.list.rows,]
}
}
#Define other terms for plotting
m = length(plot.rows)
dists = as.numeric(plot.list[[1]][,"pos"])[c(2:m)] -
as.numeric(plot.list[[1]][,"pos"])[c(1:(m - 1))]
dists = c(0, dists)
cumdists = cumsum(dists)
#Loess smoothing for plotting purposes
x.list = vector("list", length(plot.list))
smoothed.list = vector("list", length(plot.list))
names(x.list) = names(plot.list)
names(smoothed.list) = names(plot.list)
for (i in c(1:length(smoothed.list)))
{
loess.xvals = cumdists
loess.start = min(loess.xvals)
loess.xvals = loess.xvals - loess.start
loess.n = length(loess.xvals)
expand.loess.xvals = c(-loess.xvals[(expand.size + 1):2],
loess.xvals, ((2 * max(loess.xvals)) - loess.xvals[(loess.n - 1):(loess.n - expand.size - 1)]))
loess.yvals = as.numeric(plot.list[[i]][,plot.column])
expand.loess.yvals = c(loess.yvals[(expand.size + 1):2],
loess.yvals, loess.yvals[(loess.n - 1):(loess.n - expand.size - 1)])
temp.loess2 = loess(expand.loess.yvals ~ expand.loess.xvals,
span = loess.span/length(expand.loess.xvals), degree = 1, family = "gaussian")
temp.xvals = (temp.loess2$x[(expand.size + 1):(expand.size + loess.n)] + loess.start)
temp.yvals = temp.loess2$fitted[(expand.size + 1):(expand.size + loess.n)]
x.list[[i]] = (temp.xvals + as.numeric(plot.list[[i]][1, "pos"]))/1e6
smoothed.list[[i]] = temp.yvals
}
x.vals = sort(unlist(x.list))
#Create a vector of y-coordinates, then define the limits on the y-axis
plot.vals = c()
for (i in (1:length(smoothed.list)))
{
plot.vals = c(plot.vals, as.numeric(smoothed.list[[i]]))
}
if (!is.null(ylim.low))
{
ylim.low = min(ylim.low, min(plot.vals)) - vert.pad
} else ylim.low = min(plot.vals) - vert.pad
if (!is.null(ylim.high))
{
ylim.high = max(ylim.high, max(plot.vals)) + vert.pad
} else ylim.high = max(plot.vals) + vert.pad
plot(x.vals,
rep(0, length(x.vals)),
xlim = range(x.vals),
ylim = c(ylim.low, ylim.high),
axes = FALSE,
ylab = "",
xlab = "",
type = "n")
if (is.null(lty.vec))
{
lty.vec = rep(1, length(smoothed.list))
}
if (is.null(lwd.vec))
{
lwd.vec = rep(1, length(smoothed.list))
}
for (i in c(1:length(smoothed.list)))
{
lines(x.list[[i]], smoothed.list[[i]], lwd = lwd.vec[i],
col = annot.colors[i], lty = lty.vec[i])
}
axis(side = 1, cex.axis = axis.cex)
axis(side = 2, cex.axis = axis.cex)
mtext(xaxis.label, side = 1, cex = label.cex, line = xaxis.line)
mtext(yaxis.label, side = 2, cex = label.cex, line = yaxis.line)
mtext(main.label, side = 3, cex = label.cex, line = main.line)
if (plot.legend)
{
legend(legend.loc, lwd = rep(3, length(smoothed.list)),
col = annot.colors[c(1:length(smoothed.list))], names(smoothed.list),
bty = "n", inset = .05, lty = lty.vec)
}
}
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