tabulate.top.indep.features {SIM} | R Documentation |
Lists the mean z-scores for independent features in the analyzed regions, calculated across the significant dependent features. Gives insight in the expression levels most strongly associated with copy number changes.
tabulate.top.indep.features(input.regions = "all chrs", input.region.indep = NULL, method = c("full", "smooth", "window", "overlap"), adjust.method = "BY", significance = 1, decreasing=TRUE, z.threshold = c(0, 0), run.name = "analysis_results")
input.regions |
|
input.region.indep |
fill in |
method |
this must be the either one of “full”, “window”, “overlap” or “smooth” but the data should generated by the
same method in |
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. |
significance |
threshold used to select the significant dependent features. Only the z-scores with these features are used to calculate the mean z-scores across the independent features. |
decreasing |
fill in |
z.threshold |
fill in |
run.name |
This must be the same a given to |
tabulate.top.indep.features
can only be run after integrated.analysis
with zscores = TRUE
.
Output is a .txt file containing a table with the mean z-scores of all independent features
per analyzed region. It includes the ann.indep
columns that were read in the
assemble.data function.
Additionally it returns a .txt file containing the significant zscores rich regions.
Depending on the argument "adjust.method", the P-values are first corrected for multiple testing. Next, th e z-scores are filtered to include only those entries that correspond to significant (P-value < "significa nce") dependent features to calculate the mean z-scores.
The dependent table can not be generated for diagonal integrated runs.
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.dep.features
#first run example(assemble.data) #and example(integrated.analysis) table.indep <- tabulate.top.indep.features(input.regions="8q", adjust.method="BY", method="full", significance= 0.05, z.threshold=c(-1, 1), run.name="chr8q") head(table.indep[["8q"]])