Description Usage Arguments Value Author(s) Examples
Draw scatter plots for top results in whole-genome-wide analysis to test for the association of probes to a continuous-type phenotype variable.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
resFrame |
A data frame stores testing results, which must contain columns that indicate probe id, test statistic, p-value and optionally adjusted p-value. |
es |
An |
col.resFrame |
A vector of characters indicating column names of |
var.pheno |
character. the name of continuous-type phenotype variable that is used to test the association of this variable to probes. |
var.probe |
character. the name of feature variable indicating probe id. |
var.gene |
character. the name of feature variable indicating gene symbol. |
var.chr |
character. the name of feature variable indicating chromosome number. |
nTop |
integer. indicating how many top tests will be used to draw the scatter plot. |
myylab |
character. indicating y-axis label. |
datExtrFunc |
name of the function to extract genomic data. For
an |
fileFlag |
logic. indicating if plot should be saved to an external figure file. |
fileFormat |
character. indicating the figure file type. Possible values are “ps”, “pdf”, or “jpeg”. All other values will produce “png” file. |
fileName |
character. indicating figure file name (file extension should be specified). For example,
you set |
Value 0
will be returned if no error occurs.
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 | # 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)
res.limma = lmFitWrapper(
es = es.sim,
formula = ~as.factor(memSubj),
pos.var.interest = 1,
pvalAdjMethod = "fdr",
alpha = 0.05,
probeID.var = "probe",
gene.var = "gene",
chr.var = "chr",
verbose = TRUE)
boxPlots(
resFrame=res.limma$frame,
es=es.sim,
col.resFrame = c("probeIDs", "stats", "pval"),
var.pheno = "memSubj",
var.probe = "probe",
var.gene = "gene",
var.chr = "chr",
nTop = 20,
myylab = "expression level",
datExtrFunc = exprs,
fileFlag = FALSE,
fileFormat = "ps",
fileName = "boxPlots.ps")
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