Input

• (Step 1): Input a list of SNPs (i.e. dbSNP rsIDs in 1st column) with the significance information (p-values between 0 and 1 in 2nd column); for example,  Example Input. If the input is invalid, the error messages will be prompted.
• (Step 2): Specify the population to include SNPs in linkage disequilibrium. By default, input SNPs with p-value < 5e−8 are considered, and additional SNPs in linkage disequilibrium (R2 >= 0.8) can be included according to the population specified.
• (Step 3): Use genomic proximity, quantitative trait locus mapping, or promoter capture Hi-C to identify linked genes.
• (Steps 4 and 5): Identify a subnetwork of highly-scored genes from a gene network (Step 4), with the desired number of genes in the resulting subnetwork (Step 5). The significance (p-value) of observing the identified subnetwork by chance can also be estimated using a degree-preserving node permutation test.
• (More Controls) More parameters for fine-tuning steps described above.

Output

• ( Example Output) includes interactive tables and high-quality figures for the resulting subnetwork. A summary of the input data and the runtime (computed on the server side) is also returned for reference.

Other information

• The text box at Step 1 is pre-filled with the provided example when the interface page is first-visited or refreshed.
• When the user clicks on any text area within the box FOR THE FIRST TIME, the pre-filled example DISAPPEARS, and the text box is ready to receive user-input data.
• Before clicking the SUBMIT button, please replace the example with your own data EVERY TIME.
• For bug reports and inquiries, please send an email to get your feedback (also we want to learn about strengths and weaknesses).