Description Usage Arguments Details Value Author(s) See Also Examples
View source: R/tabulate.top.dep.features.R
Lists the integrated analysis P-values for the dependent features in the analyzed regions, together with the available annotation.
1 2 3 4 5 | tabulate.top.dep.features(input.regions = "all chrs",
adjust.method="BY",
method = c("full", "smooth", "window", "overlap"),
significance = 1,
run.name = "analysis_results")
|
input.regions |
|
adjust.method |
Method used to adjust the P-values for multiple testing, see p.adjust. Default is “BY” recommended when copy number is used as dependent data. See SIM for more information about adjusting P-values. |
method |
this must be the either one of “full”, “window”, “overlap” or “smooth” but the data should generated by the
same method in |
significance |
threshold used to select the significant dependent features. Pvalues below this threshold will be used to estimate regions. |
run.name |
This must be the same a given to |
Output is a .txt file containing a table with sorted integrated analysis P-values of the
dependent features. It includes the ann.dep
columns that were read in the assemble.data function.
Additionally it returns a .txt file containing the significant P-value rich regions. No P-value rich regions are returned when zscores.diag = "all"
.
Returns a list
of data.frame
's for each input region.
Significant P-value rich regions are returned as a data.frame
.
This data.frame can be used as an input for getoverlappingregions.
Additionally, the results are stored in a subdirectory of run.name
as txt.
Marten Boetzer, Melle Sieswerda, Renee X. de Menezes R.X.Menezes@lumc.nl
SIM, tabulate.pvals, tabulate.top.indep.features
1 2 3 4 5 6 7 8 9 | #first run example(assemble.data)
#and example(integrated.analysis)
#get the top dependent features sorted by p-value
table.dep <- tabulate.top.dep.features(input.regions="8q",
adjust.method="BY",
method="full",
significance=0.05,
run.name="chr8q")
head(table.dep[["8q"]])
|
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