Biomedical Informatics Institute

I Quick start

1. The first step

(1) The users can enter a gene symbol in ‘Gene symbol’text box. The inputs only have the option of using official gene symbol.

(2) The users can click the 'Survival analysis' button.

(3) 'Data source' provides dataset options. The users can choose to evaluate the gene in an individual cohort or all cohorts according to their needs.

2. The second step

(1) Base on the expression of input gene, by clicking the ‘Survival analysis’ button, the server will take the request and return the analysis results, which are graphically displayed and presented with HR and 95% CI in all the cohorts (cutoff: upper 50% vs. other 50%).

(2) The users can click the 'Go' hyperlink. After then, the server will enter detail page of the cohort.

II Advanced application

1. The first step

(1) The users can enter a gene symbol in ‘Gene symbol’text box. The inputs only have the option of using official gene symbol.

(2) 'Data source' provides dataset options. The users can choose to evaluate the gene in an individual cohort or a combined cohort according to their needs.

(3) Under 'Survival' option, 6 distinct types of survival terms are provided.

(4) By 'Spilt patients' dialog, user could select different thresholds of gene expression levels to divide patients into two subgroups of input gene.

(5) In addition, some clinical factors including TNM, gender, Alcohol, Race, etc. risk factors were set as optional factors to filter patients for special purpose from different clinicians and researchers.

(6) The users can click the 'Kaplan-Meier plot' button.

2. The second step

(1) Base on the expression of input gene, some candidate thresholds are set for this parameter. After then, by clicking the ‘Kaplan-Meier plot’ button, the server will take the request and return the analysis results, which are graphically displayed and presented with HR, 95% CI and p value.