Explore cross-species datasets from the SSPsyGene project
- Up/down-regulation split in cross-study ranking — pick a direction to filter the meta-analysis.
- Per-column filters in full-dataset tables — filter any column by text or numeric range.
- Faster, more meaningful volcano plots — background filtered by perturbed gene and sampled on the fly.
- Controls are searchable — type
CONTROLto match all controls, or search named ones (NonTarget1, SafeTarget, …) directly. - New "How gene names are parsed" doc page — covers ENSG → symbol, GENCODE clones, and silencer rules.
The SSPsyGene knowledge base brings together neuropsychiatric-genetics data generated by the SSPsyGene consortium — differential-expression studies, perturbation screens (CRISPR knockouts, knockdowns, overexpression), and phenotype annotations from human, mouse, and zebrafish models of psychiatric disease.
Search for a gene as perturbed (the gene that was experimentally manipulated — CRISPRi/CRISPRa, RNAi, knockout, mutant line) or as target(the readout whose expression or activity was measured), or fill in both fields to find consortium data on a specific perturbation→readout pair — e.g. “what happens to CNR1 when FOXG1is knocked down?”. Use the cross-study significance ranking to see which genes are most consistently implicated across the whole consortium. You can also view full datasets or look through the contributing publications.
Each dataset's table shows both nominal p-values from the source paper's analysis and a multiple-testing-corrected significance column (typically Benjamini–Hochberg FDR-adjusted) — hover any column header to see the exact statistical method and correction used. The cross-study significance ranking, by contrast, combines unadjustedper-study p-values, so its combined values can be far smaller than any single study's adjusted p-value (see methods for details).