boxPlots {iCheck} | R Documentation |
Draw scatter plots for top results in whole-genome-wide analysis to test for the association of probes to a continuous-type phenotype variable.
boxPlots( resFrame, es, col.resFrame = c("probeIDs", "stats", "pval", "p.adj"), var.pheno = "sex", var.probe = "TargetID", var.gene = "Symbol", var.chr = "Chr", nTop = 20, myylab = "expression level", datExtrFunc = exprs, fileFlag = FALSE, fileFormat = "ps", fileName = "boxPlots.ps")
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>
# 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")