Description Usage Arguments Value Author(s) Examples
Draw heatmap of square of correlations among arrays.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | R2PlotFunc(
es,
hybName = "Hybridization_Name",
arrayType = c("all", "replicates", "GC"),
GCid = c("128115", "Hela", "Brain"),
probs = seq(0, 1, 0.25),
col = gplots::greenred(75),
labelVariable = "subjID",
outFileName = "test_R2_raw.pdf",
title = "Raw Data R^2 Plot",
requireLog2 = FALSE,
plotOutPutFlag = FALSE,
las = 2,
keysize = 1,
margins = c(10, 10),
sortFlag = TRUE,
varSort=c("Batch_Run_Date", "Chip_Barcode", "Chip_Address"),
timeFormat=c("%m/%d/%Y", NA, NA),
...)
|
es |
ExpressionSet object of QC probe profiles. |
hybName |
character string. indicating the phenotype variable |
arrayType |
A character string indicating if the correlations are calculated based on all arrays, arrays with replicates, or genetic control arrays. |
GCid |
A vector of character string. symbols for genetic control samples. The symbols can be more than one. |
probs |
A vector of probabilities specify the quantiles of correlations to be output. |
col |
colors used for the image. see the function |
labelVariable |
A character string indicating how to label the arrays. |
outFileName |
A character string. The name of output file. |
title |
Title of the plot. |
requireLog2 |
logical. |
plotOutPutFlag |
logical. |
las |
'las' numeric in 0,1,2,3; the style of axis labels. 0 - always parallel to the axis, 1 - always horizontal, 2 - always perpendicular to the axis, or 3 - always vertical. see |
keysize |
numeric value indicating the size of the key.
see the function |
margins |
numeric vector of length 2 containing the margins.
see the function |
sortFlag |
logical. Indicates if arrays need to be sorted according to
|
varSort |
A vector of phenotype variable names to be used to sort the samples
of |
timeFormat |
A vector of time format for the possible time variables in |
... |
Arguments to be passed to |
A list with 3 elments. The first element R2Mat
is
the matrix of squared correlation.
The second element R2vec
is the vector of
the upper triangle of the matrix
of squared correlation (diagnoal elements are excluded).
The third element R2vec.within.req
is the vector of
within-replicate R^2,
that is, any element in R2vec.within.req
is the squared correlation
coefficient between two arrays/replicates for a subject.
Weiliang Qiu <stwxq@channing.harvard.edu>, Brandon Guo <brandowonder@gmail.com>, Christopher Anderson <christopheranderson84@gmail.com>, Barbara Klanderman <BKLANDERMAN@partners.org>, Vincent Carey <stvjc@channing.harvard.edu>, Benjamin Raby <rebar@channing.harvard.edu>
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 | # generate simulated data set from conditional normal distribution
set.seed(1234567)
es.sim = genSimData.BayesNormal(nCpGs = 100,
nCases = 20, nControls = 20,
mu.n = -2, mu.c = 2,
d0 = 20, s02 = 0.64, s02.c = 1.5, testPara = "var",
outlierFlag = FALSE,
eps = 1.0e-3, applier = lapply)
print(es.sim)
es.sim$Batch_Run_Date = 1:ncol(es.sim)
es.sim$Chip_Barcode = 1:ncol(es.sim)
es.sim$Chip_Address = 1:ncol(es.sim)
# draw heatmap for the first 5 subjects
png(file="r2plot.png")
R2PlotFunc(
es = es.sim[, 1:5],
hybName = "memSubj",
arrayType = c("all", "replicates", "GC"),
GCid = c("128115", "Hela", "Brain"),
probs = seq(0, 1, 0.25),
col = gplots::greenred(75),
labelVariable = "subjID",
outFileName = "test_R2_raw.pdf",
title = "Raw Data R^2 Plot",
requireLog2 = FALSE,
plotOutPutFlag = FALSE,
las = 2,
keysize = 1,
margins = c(10, 10),
sortFlag = TRUE,
varSort=c("Batch_Run_Date", "Chip_Barcode", "Chip_Address"),
timeFormat=c("%m/%d/%Y", NA, NA))
dev.off()
|
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