tabulate.pvals {SIM} | R Documentation |
Generates a data.frame
with the signicance of p-values in the analyzed regions, dividing them into bins.
tabulate.pvals(input.regions = "all chrs", adjust.method = "BY", bins = c(0.001, 0.005, 0.01, 0.025, 0.05, 0.075, 0.1, 0.2, 1), significance.idx = 8, order.by = "%", decreasing = TRUE, run.name = NULL)
input.regions |
vector with analyzed regions for which to produce the table.
Can be defined in four ways:
1) predefined input region: insert a predefined input region, choices are:
"all chrs" , "all chrs auto" , "all arms" , "all arms auto"
In the predefined regions "all arms" and "all arms auto" the arms 13p,
14p, 15p, 21p and 22p are left out, because in most studies there are no or few probes
in these regions. To include them, just make your own vector of arms.
2) whole chromosome(s): insert a single chromosome or a list of chromosomes as a vector:
c(1, 2, 3) .
3) chromosome arms: insert a single chromosome arm or a list of chromosome arms like
c("1q", "2p", "2q") .
4) subregions of a chromosome: insert a chromosome number followed by the start and end position lik
e c("chr1_1-1000000")
These regions can also be combined, e.g. c("chr1_1-1000000","2q", 3) .
See details for more information. |
adjust.method |
Method used to adjust the p-values for multiple
testing. Either "BY" (recommended when copy number is used as dependent data),
"BH" or "raw" . See SIM for more information about adjusting p-values. |
bins |
vector of significance thresholds. This function will calculate
the number of features having a p-value lower than the bin. |
significance.idx |
Index of "bins" to use when computing the percentage of significant p-values. Defaults to 8 (i.e. the first entry in "bins"), in this case 0.20. |
order.by |
Column used for sorting the table. Defaults to "%" (i.e. the percentage of significant p-va lues). |
decreasing |
Direction used for sorting. Defaults to TRUE (i.e. highest values on top). |
run.name |
Name of the analysis. The results will be
stored in a folder with this name in the current working directory
(use getwd() to print the current working directory).
If the run.name = NULL , the default folder "analysis_results" will be generated. |
Returns a data.frame
. Each row corresponds to a chromosome and has
as many entries as entries in bins, plus 1. Each entry contains the
number of p-values that is smaller or equal to the corresponding entry
in bins.
The last entry holds the percentage of p-values that is smaller than or
equal to the bin identified by significance.idx
.
Marten Boetzer, Melle Sieswerda, Renee X. de Menezes R.X.Menezes@lumc.nl
SIM
, assemble.data
, integrated.analysis
,
sim.plot.zscore.heatmap
, sim.plot.pvals.on.region
,
sim.plot.pvals.on.genome
, tabulate.top.dep.features
,
tabulate.top.indep.features
, impute.nas.by.surrounding
,
sim.update.chrom.table
#load the datasets and the samples to run the integrated analysis data(expr.data) data(acgh.data) data(samples) #assemble the data assemble.data(dep.data = acgh.data, indep.data = expr.data, ann.dep = 1:4,ann.indep = 1:4, dep.id="ID", dep.chr = "CHROMOSOME",dep.pos = "STARTPOS",dep.symb="Symbol", indep.id="ID",indep.chr = "CHROMOSOME", indep.pos = "STARTPOS", indep.symb="Symbol", overwrite = TRUE,run.name = "chr8") #run the integrated analysis integrated.analysis(samples = samples, input.regions = 8, adjust = FALSE, zscores=TRUE, method = "auto",run.name = "chr8") #tabulate the p-values per region tabulate.pvals(input.regions = 8,adjust.method="BY", bins=c(0.001,0.005,0.01,0.025,0.05,0.075,0.10,0.20,1.0), significance.idx=8, order.by="%", decreasing=TRUE, run.name = "chr8")