Plot line thickness:
Plot text size:
Plot text format:
Plot title:
P-value position:
Legend position:
Export plot data as text:
Generate high resolution TIFF file:
Invert HR values below 1:

More options

Compute median over entire dataset:
Backward reference:

Affy id/ Gene symbol:

Use multiple genes

	Use list of genes			Use mean expression of selected genes
	Use ratio of two genes			Filter by median expression

more genes param

Example

Example input for multiple genes:
1007_s_at 1
200000_s_at -1
31637_s_at 0.5
40016_g_at -2

Explanation:
first: normal,
second: gene is inverted,
third: gene has weight,
fourth: gene has weight and is inverted

You can also use following format:
1007_s_at, 1
200000_s_at, -1
31637_s_at, 0.5
40016_g_at, -2

Split patients by
	Auto select best cutoff
	Trichotomization
Survival:		Compute median survival:
Follow up threshold:		Censore at threshold:

Probe set options

Use

	user selected probe set
	all probe sets per gene
	only JetSet best probe set

Plot beeswarm graph of probe distribution:

Restrict analysis to subtypes...

ER status - IHC: (n=5667)
ER status - array: (n=7535)
PR status - IHC: (n=3548)
HER2 status - array: (n=7535)
Subtype - StGallen: (n=7535)
Subtype - PAM50: (n=7535)
Lymph node status: (n=4994)
Grade: (n=4429)
TP53 status: (n=660)
Pietenpol subtype: (n=2041)

Restrict analysis to selected cohorts...

	systemically untreated patients:
	patients with following systemic treatment:
	endocrine therapy:
	chemotherapy:
	patient cohort similar to SEER prevalences

Use following dataset for the analysis:

Please note: the generated p value does not include correction for multiple hypothesis testing by default.

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Please kindly cite following paper to support further development: Posta M, Gyorffy B: Pathway-level mutational signatures predict breast cancer outcomes and reveal therapeutic targets, Brit J Pharmacol, 2025

Processing...

Use multiple genes

Example

Probe set options

Restrict analysis to subtypes...

Restrict analysis to selected cohorts...