​

Genomic Elements

The IGVF Catalog contains genomic elements, which are potential functional regions for regulating gene expression. These elements are identified/tested by functional assays (e.g., MPRA), association studies (e.g., caQTLs), and computational predictions (e.g., the ENCODE-rE2G model). Data sources include:

• ENCODE Candidate Cis-Regulatory Elements (cCREs): A unified set of genomic elements predicted to have regulatory potential based on a combination of experimental data (e.g., ChIP-seq, DNase-seq) from the ENCODE project.

Additional genomic elements are added when studied in specific contexts, for example accessible elements used in predictive modeels or elements tested in an MPRA experiment or CRISPR screen

​

Genomic Elements-Genes Edges

Source	Class	Edge Description	Datasets
ENCODE	prediction	Biosample specific enhancer-gene predictions using rE2G pipeline	ENCODE-rE2G
IGVF	observed data	CRISPRa and CRISPRi Perturb-seq integrating a guide (sgRNA) library targeting transcription start sites in 24 genes in CD8-positive, alpha-beta memory T primary cells	IGVF Perturb-seq assays
IGVF	observed data	CRISPRi CRISPRa CRISPRko FACS screen of CCR7 and IL7R inCD8-positive, alpha-beta memory T primary cells	IGVF CRISPR FACS screen

​

Genomic Elements-Biosamples Edges

Source	Class	Edge Description	Datasets
ENCODE	observed data	lentiMPRA testing potential HepG2, K562, and WTC11 enhancers and promoters of all protein-coding genes.	ENCODE lentiMPRA
IGVF	observed data	lentiMPRA in 5 biosamples measuring effect of element (and variants) on gene expression	IGVF lentiMPRA

​

Variants-Genomic Elements Edges

(also on variants page)

• External caQTL studies: variants associated with genomic elements function from external studies (PMID:34038741, PMID:34017130) and AFGR(African Functional Genomics Resource)
• IGVF BlueSTARR: computational model predicts variants affecting the regulatory function in ENCODE cCREs (Candidate Cis-Regulatory Elements)
• IGVF MPRA

​

Table Columns:

Column	Description
Region	Genomic coordinates of the regulatory region (clickable for more details)
Biochemical Activity	The type of biochemical activity in this region
Biochemical Activity Description	Detailed description of the biochemical activity
Type	Classification of the regulatory region
Source	Origin of the data
Source URL	Link to the original data source (clickable)

​

Interacting with the Table:

• Click on column headers to sort the table by that column
• Use the search box above the table to filter results
• Adjust the number of rows displayed using the dropdown menu
• Navigate between pages using the “Previous” and “Next” buttons

​

Biosample Table

The Biosample Table provides information about biological samples associated with the regulatory regions in your selected genomic coordinates.

​

Table Columns:

Column	Description
Activity Score	Numerical score indicating the level of activity (higher is more active)
Source	Origin of the biosample data (clickable link)
Chromosome, Region Start, Region End	Location of the associated regulatory region
Region Name, Region Type	Identifiers for the regulatory region
Biochemical Activity, Activity Description	Details about the biochemical activity in the region
Biosample Name	Name of the biological sample
Term ID	Unique identifier for the biosample
Description	Detailed description of the biosample
Biosample Source	Origin of the biosample
Subontology	Subclassification of the biosample, if applicable

​

Enhancer-Gene Prediction(s)

This table reports whether the query region contains predicted enhancers from the ENCODE-rE2G model, and their target genes and cell types. Each row reports one predicted enhancer, target gene, and cell type.

Column	Description
Cell Type	Cell type in which the enhancer is predicted to regulate the gene
Target Gene	Gene predicted to be regulated by the enhancer
Score	Strength of the prediction (range: 0 to 1, higher indicates a more confident prediction)
Dataset	Source dataset
Model	Predictive model. Currently: ENCODE-rE2G
Variant-Gene Distance	Genomic distance between the variant and gene body

Currently, this table includes predictions from the ENCODE-rE2G model across 1700+ ENCODE biosamples (see Gschwind et al. bioRxiv 2023) The table is initially sorted by Score in descending order, showing the strongest predictions first.