New ! Human enhancer to target gene assignments (hg19 and hg38): We now include distal enhancer to target gene assignments by combining multiple spatial and in silico approaches for defining enhancer locations and linking them to their target genes, aggregated across >500 cell types. In a comprehensive comparison, this approach was shown to significantly outperform the simple nearest TSS approach.
PolyEnrich method is required with these new enhancer to target gene links.
ChIP-Enrich and Poly-Enrich test ChIP-seq peak data for enrichment of biological pathways,
Gene Ontology terms, and other types of gene sets. Using an input .BED file,
ChIP-Enrich and Poly-Enrich assign peaks to genes based on a chosen "locus definition".
The "locus" of a gene is the region from which the gene is predicted to be regulated.
ChIP-Enrich uses a logistic regression model to test for association between the
presence of at least one peak in a gene and gene set membership, while Poly-Enrich
uses a negative binomial regression model to test the association between the number
of peaks in a gene and gene set membership. They empirically adjust for the relationship
between the length of the loci (and optionally mappability) and the outcome using
a cubic smoothing spline term within the logistic model. Detailed methods are provided here.
Output includes summary plots, peak to gene assignments,and enrichment (and depletion)
results including odds ratio, p-value, and FDR for each gene set.
If your data set consists of broad genomic regions or covers a significant portion of the total genome,
we recommend using Broad-Enrich instead.