V2FKP Epigenetic and Computational Datasets

Many of the results listed below are generated by computational methods that predict associations between different entities: variants; genes or gene sets; tissues or cell lines; and phenotypes (diseases or traits).

Variantsvariant Genesgene Phenotypesphenotype   Tissuestissue Gene sets or pathwaysGene sets icon

 

Dataset name in V2FKP Description and reference Entities connected Access dataset
ABC Enhancer Maps

Enhancer-gene pairs from roughly 150 cell types, predicted by the ABC method; DNAse I hypersensitivity annotations; CTCF binding motifs; and promoters.

Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations. Fulco CP, Nasser J, et al., 2019, PMID:31784727.

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Allele-specific ATAC-seq annotations for lymphoblastoid cell lines

Genome-wide chromatin accessibility landscapes in 24 lymphoblastoid cell lines from the 1000 Genomes GBR population, generated using ATAC-seq.

Fine-mapping Cellular QTLs With RASQUAL and ATAC-seq. Kumasaka N, et al., 2016, PMID:26656845.

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Allele-specific ATAC-seq annotations for activated CD4+ T cells

ATAC-seq on stimulated CD4+ T cells from 105 healthy individuals.

Genetic Determinants of Co-Accessible Chromatin Regions in Activated T Cells Across Humans. Gate R, et al., 2018, PMID:29988122.

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Allele-specific DNAse I hypersensitivity annotations for lymphoblastoid cell lines

Chromatin accessibility in 70 Yoruba lymphoblastoid cell lines (LCLs) measured by DNaseI sequencing and compared with genotype to generate DNaseI sensitivity Quantitative Trait Loci, dsQTLs.

DNase I Sensitivity QTLs Are a Major Determinant of Human Expression Variation. Degner JF, et al., 2012, PMID:22307276.

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Allele-specific DNAse I hypersensitivity annotations for multiple cell lines

Integration of DNaseI footprinting data with sequence-based transcription factor (TF) motif models to predict the impact of a genetic variant on TF binding across multiple tissues.

Which Genetics Variants in DNase-Seq Footprints Are More Likely to Alter Binding? Moyerbrailean GA, et al., 2016, PMID:26901046.

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Allele-specific H3K27ac annotations for brain tissues

Histone H3K27ac modifications in cerebellum, pre-frontal cortex, and temporal cortex.

Histone Acetylome-wide Association Study of Autism Spectrum Disorder. Sun W, et al., 2016, PMID:27863250.

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Allele-specific H3K27ac annotations for immune cells

Histone H3K27ac modifications in CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells.

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells. Chen L, et al., 2016, PMID:27863251.

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Allele-specific H3K27ac annotations for lymphoblastoid cell lines

Histone H3K27ac modifications in lymphoblastoid cell lines.

Sensitive Detection of Chromatin-Altering Polymorphisms Reveals Autoimmune Disease Mechanisms. Cruz-Herrera del Rosario R, et al., 2015, PMID:25799442.

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Catalog of Inferred Sequence Binding Preferences (CIS-BP)

CIS-BP is an online library of transcription factors and their DNA binding motifs.

Determination and Inference of Eukaryotic Transcription Factor Sequence Specificity. Weirauch MT, et al., 2014, PMID:25215497.

 

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HaploReg

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks.

HaploReg v4: Systematic Mining of Putative Causal Variants, Cell Types, Regulators and Target Genes for Human Complex Traits and Disease. Ward LD, Kellis M, 2016, PMID:26657631.

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LD score regression annotations

LD score regression (LDSR) uses cell type-specific annotations and genetic
association summary statistics to find phenotype-specific cell type enrichments
while accounting for linked markers.

Partitioning Heritability by Functional Annotation Using Genome-Wide Association Summary Statistics. Finucane H, et al., 2015. PMID:26414678.

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Roadmap Epigenomics and ENCODE ChromHMM chromatin states

Regions delineated using observed DNaseI data across 53 epigenomes, annotated with the 5-mark 15-state model based on imputed data across 127 epigenomes (Roadmap + ENCODE).

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Single-nucleus ATAC-seq

Mapping accessible chromatin profiles of individual islet cells using snATAC-seq.

Single cell chromatin accessibility reveals pancreatic islet cell type2 and state-specific regulatory programs of diabetes risk. Chiou J, et al., 2020, BioRxiv.

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UK Biobank Fine-Mapping

Genome-wide association analysis was performed for multiple traits in the UK Biobank population; then fine-mapping was performed to statistically identify causal variants.

Unpublished; see documentation.

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