Home:

Users can input your interested gene and then click "Go!" button. they will get a comprehensive search result.

SNP:

PGC2 GWAS & PGC3 GWAS

Users can input some SNPs (one SNP per line) or a genome position and then click "search" button. they will get the results .

Functional SNPs

In this module, users only need to input some SNPs (one SNP per line). they will get the results like figure1.

Figure 1. Options for SNP search and SNP search result.

Gene:

Gene Browser System

In this module, we used the dropdown navigation to visit the Gene Browser System pages.

Genes identified by SMR

In this module, users need to do the following 3 steps: 1. Select PGC2 or PGC3; 2. Select a brain eQTL dataset; 3. Input genes (one gene per line);

Genes identified by TWAS

In this module, users need to do the following 3 steps: 1. Select PGC2 or PGC3; 2. Select a brain eQTL dataset; 3. Input genes (one gene per line);

Genes identified by GWAS

    In this module, users need to select a GWAS and input interested genes (one gene per line) or input a region.

Genes identified by CNVs

In this module, users need to input interested genes (one gene per line) or select interested cytoband or input interested region.

Genes identified by Exome/Genome Sequencing

    In this module, users need to do the following 2 steps: 1. Select de novo or rare; 2. Input genes(one gene per line).

Genes expressed differentially in PsychENCODE

In this module, users only need to input interested genes (one gene per line). In the results page, users can click boxplot to show the box picture.

Analysis:

Static LocusZoom

In this module, users only need to input a SNP or input a interested gene.

Gene eQTL query

In this module, users need to do the following 2 steps: 1. Select a dataset; 2.Input genes(one gene per line) or input SNPs(one SNP per line)

Transcript eQTL query

In this module, users need to do the following 2 steps: 1. Select a dataset; 2.Input transcript ids(one transcript id per line) or input SNPs(one SNP per line) .

Protein-Protein Interaction

In this module, users need to do the following 2 steps: 1.Input genes(one gene per line); 2.Select a display type.

Co-expression analysis

In this module, users need to do the following 2 steps: 1.Input genes(one gene per line); 2.Select a minimum pearson correlation coefficient

Expression pattern analysis

In this module, users need to do the following 2 steps: 1.Input genes(one gene per line); 2.Select a dataset.

Tissue expression analysis

    In this module, users only need to input a interested gene.