plot.hrunbiasedTesting: Plotting Cox proportional hazard model outcome for gene...

In adricaba/hrunbiased: Survival analysis for gene signatures

Description

Plot function for hrunbiasedTesting objects

Usage

## S3 method for class 'hrunbiasedTesting'
plot(x, legend.out = TRUE, show.pvalues = TRUE,
          show.stat = TRUE,  density.tg.minpoints = 10, ...)

Arguments

x	Object of class hrunbiasedTesting
legend.out	If TRUE, an automatic legend is shown in the plot
show.pvalues	If TRUE, an automatic legend with the testing p-values is created
show.stat	If TRUE, the hazard ratio statistic is shown, if FALSE, the log hazard ratio is shown
density.tg.minpoints	minimum number of genes to show a density estimation of the signature hazard ratios genewise
...	Arguments passed to or from other methods to the low level

Value

plot of object of class hrunbiasedTesting.

Author(s)

Adria Caballe Mestres

References

Caballe Mestres A, Berenguer Llergo A and Stephan-Otto Attolini C. Adjusting for systematic technical biases in risk assessment of gene signatures in transcriptomic cancer cohorts. bioRxiv (2018).

See Also

hrunbiasedTesting and hrunbiasedDiagnostic

Examples

eh <- ExperimentHub()
nda.brca <- query(eh, "mcsurvdata")[["EH1497"]]
nda.gse1456 <- nda.brca[,nda.brca$dataset=="GSE1456"]
data(mammaprint.sig)
mammaprint.sig <- intersect(mammaprint.sig, rownames(nda.gse1456))
correction.type <-  "Gsignature"
tout.GS <- hrunbiasedTesting(nda.gse1456,
    gene.signature = mammaprint.sig, test.type = c("asymptotic",
    "random.signatures", "random.genes"), correction.type = "Gsignature",
    mc.cores=1, nrs = 100, executation.info = FALSE)
plot(tout.GS)

adricaba/hrunbiased documentation built on May 24, 2019, 7:48 a.m.