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:

Restrict analysis to subtypes...


Lymph node status: (n=2887)
ER status: (n=2789)
PGR status: (n=2662)
HER2 status: (n=2875)
KI67 status: (n=1360)
Nottingham histologic grade: (n=2917)
PAM50 subtype: (n=2976)

Restrict analysis to selected cohorts...


Endocrine treated: (n=2955)
Chemo treated: (n=2956)

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: Győrffy B. Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer, Computational and Structural Biotechnology Journal, 2021;19:4101-4109, https://doi.org/10.1016/j.csbj.2021.07.014

Plot line thickness:
Plot text size:
Plot text format:
Plot title:
P-value position:
Legend position:

Generate high resolution TIFF file:
Invert HR values below 1:
Export plot data as text:

Compute median over entire dataset:
Backward reference:

Processing...

Use multiple genes

Example

Restrict analysis to subtypes...

Restrict analysis to selected cohorts...