Annotations capturing cell-type-specific TF binding explain a large fraction of disease heritability Article Swipe
Bryce van de Geijn
,
Hilary K. Finucane
,
Steven Gazal
,
Farhad Hormozdiari
,
Tiffany Amariuta
,
Xuanyao Liu
,
Alexander Gusev
,
Po‐Ru Loh
,
Yakir Reshef
,
Gleb Kichaev
,
Soumya Raychauduri
,
Alkes L. Price
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/474684
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1101/474684
It is widely known that regulatory variation plays a major role in complex disease and that cell-type-specific binding of transcription factors (TF) is critical to gene regulation, but genomic annotations from directly measured TF binding information are not currently available for most cell-type-TF pairs. Here, we construct cell-type-specific TF binding annotations by intersecting sequence-based TF binding predictions with cell-type-specific chromatin data; this strategy addresses both the limitation that identical sequences may be bound or unbound depending on surrounding chromatin context, and the limitation that sequence-based predictions are generally not cell-type-specific. We evaluated different combinations of sequence-based TF predictions and chromatin data by partitioning the heritability of 49 diseases and complex traits (average N=320K) using stratified LD score regression with the baseline-LD model (which is not cell-type-specific). We determined that 100bp windows around MotifMap sequenced-based TF binding predictions intersected with a union of six cell-type-specific chromatin marks (imputed using ChromImpute) performed best, with an 58% increase in heritability enrichment compared to the chromatin marks alone (11.6x vs 7.3x; P = 9 × 10 -14 for difference) and a 12% increase in cell-type-specific signal conditional on annotations from the baseline-LD model (P = 8 × 10 -11 for difference). Our results show that intersecting sequence-based TF predictions with cell-type-specific chromatin information can help refine genome-wide association signals.
Related Topics
Concepts
Chromatin
Transcription factor
Biology
Cell type
Heritability
Genetics
Computational biology
Chromatin immunoprecipitation
Gene
Cell
Gene expression
Promoter
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/474684
- https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdf
- OA Status
- green
- Cited By
- 6
- References
- 52
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2900789301
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2900789301Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/474684Digital Object Identifier
- Title
-
Annotations capturing cell-type-specific TF binding explain a large fraction of disease heritabilityWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2018Year of publication
- Publication date
-
2018-11-20Full publication date if available
- Authors
-
Bryce van de Geijn, Hilary K. Finucane, Steven Gazal, Farhad Hormozdiari, Tiffany Amariuta, Xuanyao Liu, Alexander Gusev, Po‐Ru Loh, Yakir Reshef, Gleb Kichaev, Soumya Raychauduri, Alkes L. PriceList of authors in order
- Landing page
-
https://doi.org/10.1101/474684Publisher landing page
- PDF URL
-
https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdfDirect OA link when available
- Concepts
-
Chromatin, Transcription factor, Biology, Cell type, Heritability, Genetics, Computational biology, Chromatin immunoprecipitation, Gene, Cell, Gene expression, PromoterTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
6Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 3, 2021: 1, 2020: 1, 2019: 1Per-year citation counts (last 5 years)
- References (count)
-
52Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W2900789301 |
|---|---|
| doi | https://doi.org/10.1101/474684 |
| ids.doi | https://doi.org/10.1101/474684 |
| ids.mag | 2900789301 |
| ids.openalex | https://openalex.org/W2900789301 |
| fwci | 0.32131384 |
| type | preprint |
| title | Annotations capturing cell-type-specific TF binding explain a large fraction of disease heritability |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T10222 |
| topics[0].field.id | https://openalex.org/fields/13 |
| topics[0].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[0].score | 0.9993000030517578 |
| topics[0].domain.id | https://openalex.org/domains/1 |
| topics[0].domain.display_name | Life Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1312 |
| topics[0].subfield.display_name | Molecular Biology |
| topics[0].display_name | Genomics and Chromatin Dynamics |
| topics[1].id | https://openalex.org/T10261 |
| topics[1].field.id | https://openalex.org/fields/13 |
| topics[1].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[1].score | 0.9851999878883362 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1311 |
| topics[1].subfield.display_name | Genetics |
| topics[1].display_name | Genetic Associations and Epidemiology |
| topics[2].id | https://openalex.org/T11213 |
| topics[2].field.id | https://openalex.org/fields/13 |
| topics[2].field.display_name | Biochemistry, Genetics and Molecular Biology |
| topics[2].score | 0.9786999821662903 |
| topics[2].domain.id | https://openalex.org/domains/1 |
| topics[2].domain.display_name | Life Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1311 |
| topics[2].subfield.display_name | Genetics |
| topics[2].display_name | Genomic variations and chromosomal abnormalities |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C83640560 |
| concepts[0].level | 3 |
| concepts[0].score | 0.780451774597168 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q180951 |
| concepts[0].display_name | Chromatin |
| concepts[1].id | https://openalex.org/C86339819 |
| concepts[1].level | 3 |
| concepts[1].score | 0.6166732311248779 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q407384 |
| concepts[1].display_name | Transcription factor |
| concepts[2].id | https://openalex.org/C86803240 |
| concepts[2].level | 0 |
| concepts[2].score | 0.5915516018867493 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q420 |
| concepts[2].display_name | Biology |
| concepts[3].id | https://openalex.org/C189014844 |
| concepts[3].level | 3 |
| concepts[3].score | 0.5513001084327698 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q189118 |
| concepts[3].display_name | Cell type |
| concepts[4].id | https://openalex.org/C161890455 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5070681571960449 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q1503548 |
| concepts[4].display_name | Heritability |
| concepts[5].id | https://openalex.org/C54355233 |
| concepts[5].level | 1 |
| concepts[5].score | 0.5024416446685791 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q7162 |
| concepts[5].display_name | Genetics |
| concepts[6].id | https://openalex.org/C70721500 |
| concepts[6].level | 1 |
| concepts[6].score | 0.48708558082580566 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q177005 |
| concepts[6].display_name | Computational biology |
| concepts[7].id | https://openalex.org/C134320426 |
| concepts[7].level | 5 |
| concepts[7].score | 0.4488721191883087 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q901026 |
| concepts[7].display_name | Chromatin immunoprecipitation |
| concepts[8].id | https://openalex.org/C104317684 |
| concepts[8].level | 2 |
| concepts[8].score | 0.44720470905303955 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q7187 |
| concepts[8].display_name | Gene |
| concepts[9].id | https://openalex.org/C1491633281 |
| concepts[9].level | 2 |
| concepts[9].score | 0.442902147769928 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q7868 |
| concepts[9].display_name | Cell |
| concepts[10].id | https://openalex.org/C150194340 |
| concepts[10].level | 3 |
| concepts[10].score | 0.2029491662979126 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q26972 |
| concepts[10].display_name | Gene expression |
| concepts[11].id | https://openalex.org/C101762097 |
| concepts[11].level | 4 |
| concepts[11].score | 0.16446244716644287 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q224093 |
| concepts[11].display_name | Promoter |
| keywords[0].id | https://openalex.org/keywords/chromatin |
| keywords[0].score | 0.780451774597168 |
| keywords[0].display_name | Chromatin |
| keywords[1].id | https://openalex.org/keywords/transcription-factor |
| keywords[1].score | 0.6166732311248779 |
| keywords[1].display_name | Transcription factor |
| keywords[2].id | https://openalex.org/keywords/biology |
| keywords[2].score | 0.5915516018867493 |
| keywords[2].display_name | Biology |
| keywords[3].id | https://openalex.org/keywords/cell-type |
| keywords[3].score | 0.5513001084327698 |
| keywords[3].display_name | Cell type |
| keywords[4].id | https://openalex.org/keywords/heritability |
| keywords[4].score | 0.5070681571960449 |
| keywords[4].display_name | Heritability |
| keywords[5].id | https://openalex.org/keywords/genetics |
| keywords[5].score | 0.5024416446685791 |
| keywords[5].display_name | Genetics |
| keywords[6].id | https://openalex.org/keywords/computational-biology |
| keywords[6].score | 0.48708558082580566 |
| keywords[6].display_name | Computational biology |
| keywords[7].id | https://openalex.org/keywords/chromatin-immunoprecipitation |
| keywords[7].score | 0.4488721191883087 |
| keywords[7].display_name | Chromatin immunoprecipitation |
| keywords[8].id | https://openalex.org/keywords/gene |
| keywords[8].score | 0.44720470905303955 |
| keywords[8].display_name | Gene |
| keywords[9].id | https://openalex.org/keywords/cell |
| keywords[9].score | 0.442902147769928 |
| keywords[9].display_name | Cell |
| keywords[10].id | https://openalex.org/keywords/gene-expression |
| keywords[10].score | 0.2029491662979126 |
| keywords[10].display_name | Gene expression |
| keywords[11].id | https://openalex.org/keywords/promoter |
| keywords[11].score | 0.16446244716644287 |
| keywords[11].display_name | Promoter |
| language | en |
| locations[0].id | doi:10.1101/474684 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306402567 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | False |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| locations[0].source.host_organization | https://openalex.org/I2750212522 |
| locations[0].source.host_organization_name | Cold Spring Harbor Laboratory |
| locations[0].source.host_organization_lineage | https://openalex.org/I2750212522 |
| locations[0].license | other-oa |
| locations[0].pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdf |
| locations[0].version | acceptedVersion |
| locations[0].raw_type | posted-content |
| locations[0].license_id | https://openalex.org/licenses/other-oa |
| locations[0].is_accepted | True |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | https://doi.org/10.1101/474684 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5090083293 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-3689-8951 |
| authorships[0].author.display_name | Bryce van de Geijn |
| authorships[0].countries | US |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I136199984 |
| authorships[0].affiliations[0].raw_affiliation_string | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[0].institutions[0].id | https://openalex.org/I136199984 |
| authorships[0].institutions[0].ror | https://ror.org/03vek6s52 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I136199984 |
| authorships[0].institutions[0].country_code | US |
| authorships[0].institutions[0].display_name | Harvard University |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Bryce van de Geijn |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[1].author.id | https://openalex.org/A5021444806 |
| authorships[1].author.orcid | https://orcid.org/0000-0003-3864-9828 |
| authorships[1].author.display_name | Hilary K. Finucane |
| authorships[1].countries | US |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I107606265 |
| authorships[1].affiliations[0].raw_affiliation_string | Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA |
| authorships[1].institutions[0].id | https://openalex.org/I107606265 |
| authorships[1].institutions[0].ror | https://ror.org/05a0ya142 |
| authorships[1].institutions[0].type | nonprofit |
| authorships[1].institutions[0].lineage | https://openalex.org/I107606265 |
| authorships[1].institutions[0].country_code | US |
| authorships[1].institutions[0].display_name | Broad Institute |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Hilary Finucane |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA |
| authorships[2].author.id | https://openalex.org/A5042815092 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-4510-5730 |
| authorships[2].author.display_name | Steven Gazal |
| authorships[2].countries | US |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I136199984 |
| authorships[2].affiliations[0].raw_affiliation_string | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[2].institutions[0].id | https://openalex.org/I136199984 |
| authorships[2].institutions[0].ror | https://ror.org/03vek6s52 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I136199984 |
| authorships[2].institutions[0].country_code | US |
| authorships[2].institutions[0].display_name | Harvard University |
| authorships[2].author_position | middle |
| authorships[2].raw_author_name | Steven Gazal |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[3].author.id | https://openalex.org/A5016230870 |
| authorships[3].author.orcid | https://orcid.org/0000-0002-5617-6174 |
| authorships[3].author.display_name | Farhad Hormozdiari |
| authorships[3].countries | US |
| authorships[3].affiliations[0].institution_ids | https://openalex.org/I136199984 |
| authorships[3].affiliations[0].raw_affiliation_string | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[3].institutions[0].id | https://openalex.org/I136199984 |
| authorships[3].institutions[0].ror | https://ror.org/03vek6s52 |
| authorships[3].institutions[0].type | education |
| authorships[3].institutions[0].lineage | https://openalex.org/I136199984 |
| authorships[3].institutions[0].country_code | US |
| authorships[3].institutions[0].display_name | Harvard University |
| authorships[3].author_position | middle |
| authorships[3].raw_author_name | Farhad Hormozdiari |
| authorships[3].is_corresponding | False |
| authorships[3].raw_affiliation_strings | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[4].author.id | https://openalex.org/A5028223846 |
| authorships[4].author.orcid | https://orcid.org/0000-0003-0121-1726 |
| authorships[4].author.display_name | Tiffany Amariuta |
| authorships[4].countries | US |
| authorships[4].affiliations[0].institution_ids | https://openalex.org/I136199984, https://openalex.org/I4210155419 |
| authorships[4].affiliations[0].raw_affiliation_string | Center for Data Sciences, Harvard Medical School, Boston, MA |
| authorships[4].affiliations[1].institution_ids | https://openalex.org/I1283280774, https://openalex.org/I136199984 |
| authorships[4].affiliations[1].raw_affiliation_string | Divisions of Genetics, Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA |
| authorships[4].affiliations[2].institution_ids | https://openalex.org/I136199984 |
| authorships[4].affiliations[2].raw_affiliation_string | Department of Biomedical Informatics, Harvard Medical School, Boston, MA |
| authorships[4].affiliations[3].institution_ids | https://openalex.org/I136199984 |
| authorships[4].affiliations[3].raw_affiliation_string | Graduate School of Arts and Sciences, Harvard University, Boston, MA |
| authorships[4].institutions[0].id | https://openalex.org/I1283280774 |
| authorships[4].institutions[0].ror | https://ror.org/04b6nzv94 |
| authorships[4].institutions[0].type | healthcare |
| authorships[4].institutions[0].lineage | https://openalex.org/I1283280774, https://openalex.org/I48633490 |
| authorships[4].institutions[0].country_code | US |
| authorships[4].institutions[0].display_name | Brigham and Women's Hospital |
| authorships[4].institutions[1].id | https://openalex.org/I4210155419 |
| authorships[4].institutions[1].ror | https://ror.org/05r3dyn47 |
| authorships[4].institutions[1].type | facility |
| authorships[4].institutions[1].lineage | https://openalex.org/I136199984, https://openalex.org/I4210087915, https://openalex.org/I4210155419, https://openalex.org/I48633490 |
| authorships[4].institutions[1].country_code | US |
| authorships[4].institutions[1].display_name | Center for Systems Biology |
| authorships[4].institutions[2].id | https://openalex.org/I136199984 |
| authorships[4].institutions[2].ror | https://ror.org/03vek6s52 |
| authorships[4].institutions[2].type | education |
| authorships[4].institutions[2].lineage | https://openalex.org/I136199984 |
| authorships[4].institutions[2].country_code | US |
| authorships[4].institutions[2].display_name | Harvard University |
| authorships[4].author_position | middle |
| authorships[4].raw_author_name | Tiffany Amariuta |
| authorships[4].is_corresponding | False |
| authorships[4].raw_affiliation_strings | Center for Data Sciences, Harvard Medical School, Boston, MA, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, Divisions of Genetics, Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, Graduate School of Arts and Sciences, Harvard University, Boston, MA |
| authorships[5].author.id | https://openalex.org/A5075969050 |
| authorships[5].author.orcid | https://orcid.org/0000-0002-5955-6738 |
| authorships[5].author.display_name | Xuanyao Liu |
| authorships[5].countries | US |
| authorships[5].affiliations[0].institution_ids | https://openalex.org/I136199984 |
| authorships[5].affiliations[0].raw_affiliation_string | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[5].institutions[0].id | https://openalex.org/I136199984 |
| authorships[5].institutions[0].ror | https://ror.org/03vek6s52 |
| authorships[5].institutions[0].type | education |
| authorships[5].institutions[0].lineage | https://openalex.org/I136199984 |
| authorships[5].institutions[0].country_code | US |
| authorships[5].institutions[0].display_name | Harvard University |
| authorships[5].author_position | middle |
| authorships[5].raw_author_name | Xuanyao Liu |
| authorships[5].is_corresponding | False |
| authorships[5].raw_affiliation_strings | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[6].author.id | https://openalex.org/A5044886059 |
| authorships[6].author.orcid | https://orcid.org/0000-0002-7980-4620 |
| authorships[6].author.display_name | Alexander Gusev |
| authorships[6].countries | US |
| authorships[6].affiliations[0].institution_ids | https://openalex.org/I4210117453 |
| authorships[6].affiliations[0].raw_affiliation_string | Dana Farber Cancer Institute, Boston, MA |
| authorships[6].institutions[0].id | https://openalex.org/I4210117453 |
| authorships[6].institutions[0].ror | https://ror.org/02jzgtq86 |
| authorships[6].institutions[0].type | facility |
| authorships[6].institutions[0].lineage | https://openalex.org/I4210117453 |
| authorships[6].institutions[0].country_code | US |
| authorships[6].institutions[0].display_name | Dana-Farber Cancer Institute |
| authorships[6].author_position | middle |
| authorships[6].raw_author_name | Alexander Gusev |
| authorships[6].is_corresponding | False |
| authorships[6].raw_affiliation_strings | Dana Farber Cancer Institute, Boston, MA |
| authorships[7].author.id | https://openalex.org/A5048717316 |
| authorships[7].author.orcid | https://orcid.org/0000-0001-5542-9064 |
| authorships[7].author.display_name | Po‐Ru Loh |
| authorships[7].countries | US |
| authorships[7].affiliations[0].institution_ids | https://openalex.org/I1283280774 |
| authorships[7].affiliations[0].raw_affiliation_string | Brigham and Women's Hospital, Boston, MA |
| authorships[7].institutions[0].id | https://openalex.org/I1283280774 |
| authorships[7].institutions[0].ror | https://ror.org/04b6nzv94 |
| authorships[7].institutions[0].type | healthcare |
| authorships[7].institutions[0].lineage | https://openalex.org/I1283280774, https://openalex.org/I48633490 |
| authorships[7].institutions[0].country_code | US |
| authorships[7].institutions[0].display_name | Brigham and Women's Hospital |
| authorships[7].author_position | middle |
| authorships[7].raw_author_name | Po-Ru Loh |
| authorships[7].is_corresponding | False |
| authorships[7].raw_affiliation_strings | Brigham and Women's Hospital, Boston, MA |
| authorships[8].author.id | https://openalex.org/A5024961870 |
| authorships[8].author.orcid | https://orcid.org/0000-0001-6463-4203 |
| authorships[8].author.display_name | Yakir Reshef |
| authorships[8].countries | US |
| authorships[8].affiliations[0].institution_ids | https://openalex.org/I136199984 |
| authorships[8].affiliations[0].raw_affiliation_string | Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[8].affiliations[1].raw_affiliation_string | Harvard/MIT MD/PhD Program, Boston, MA |
| authorships[8].institutions[0].id | https://openalex.org/I136199984 |
| authorships[8].institutions[0].ror | https://ror.org/03vek6s52 |
| authorships[8].institutions[0].type | education |
| authorships[8].institutions[0].lineage | https://openalex.org/I136199984 |
| authorships[8].institutions[0].country_code | US |
| authorships[8].institutions[0].display_name | Harvard University |
| authorships[8].author_position | middle |
| authorships[8].raw_author_name | Yakir Reshef |
| authorships[8].is_corresponding | False |
| authorships[8].raw_affiliation_strings | Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, Harvard/MIT MD/PhD Program, Boston, MA |
| authorships[9].author.id | https://openalex.org/A5076033791 |
| authorships[9].author.orcid | https://orcid.org/0000-0003-3518-9950 |
| authorships[9].author.display_name | Gleb Kichaev |
| authorships[9].countries | US |
| authorships[9].affiliations[0].institution_ids | https://openalex.org/I161318765 |
| authorships[9].affiliations[0].raw_affiliation_string | Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA |
| authorships[9].institutions[0].id | https://openalex.org/I161318765 |
| authorships[9].institutions[0].ror | https://ror.org/046rm7j60 |
| authorships[9].institutions[0].type | education |
| authorships[9].institutions[0].lineage | https://openalex.org/I161318765 |
| authorships[9].institutions[0].country_code | US |
| authorships[9].institutions[0].display_name | University of California, Los Angeles |
| authorships[9].author_position | middle |
| authorships[9].raw_author_name | Gleb Kichaev |
| authorships[9].is_corresponding | False |
| authorships[9].raw_affiliation_strings | Bioinformatics Interdepartmental Program, University of California Los Angeles, Los Angeles, CA |
| authorships[10].author.id | https://openalex.org/A5051146737 |
| authorships[10].author.orcid | |
| authorships[10].author.display_name | Soumya Raychauduri |
| authorships[10].countries | US |
| authorships[10].affiliations[0].institution_ids | https://openalex.org/I136199984, https://openalex.org/I4210155419 |
| authorships[10].affiliations[0].raw_affiliation_string | Center for Data Sciences, Harvard Medical School, Boston, MA |
| authorships[10].affiliations[1].institution_ids | https://openalex.org/I136199984 |
| authorships[10].affiliations[1].raw_affiliation_string | Graduate School of Arts and Sciences, Harvard University, Boston, MA |
| authorships[10].affiliations[2].institution_ids | https://openalex.org/I136199984 |
| authorships[10].affiliations[2].raw_affiliation_string | Department of Biomedical Informatics, Harvard Medical School, Boston, MA |
| authorships[10].affiliations[3].institution_ids | https://openalex.org/I136199984 |
| authorships[10].affiliations[3].raw_affiliation_string | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[10].affiliations[4].institution_ids | https://openalex.org/I1283280774, https://openalex.org/I136199984 |
| authorships[10].affiliations[4].raw_affiliation_string | Divisions of Genetics, Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA |
| authorships[10].institutions[0].id | https://openalex.org/I1283280774 |
| authorships[10].institutions[0].ror | https://ror.org/04b6nzv94 |
| authorships[10].institutions[0].type | healthcare |
| authorships[10].institutions[0].lineage | https://openalex.org/I1283280774, https://openalex.org/I48633490 |
| authorships[10].institutions[0].country_code | US |
| authorships[10].institutions[0].display_name | Brigham and Women's Hospital |
| authorships[10].institutions[1].id | https://openalex.org/I4210155419 |
| authorships[10].institutions[1].ror | https://ror.org/05r3dyn47 |
| authorships[10].institutions[1].type | facility |
| authorships[10].institutions[1].lineage | https://openalex.org/I136199984, https://openalex.org/I4210087915, https://openalex.org/I4210155419, https://openalex.org/I48633490 |
| authorships[10].institutions[1].country_code | US |
| authorships[10].institutions[1].display_name | Center for Systems Biology |
| authorships[10].institutions[2].id | https://openalex.org/I136199984 |
| authorships[10].institutions[2].ror | https://ror.org/03vek6s52 |
| authorships[10].institutions[2].type | education |
| authorships[10].institutions[2].lineage | https://openalex.org/I136199984 |
| authorships[10].institutions[2].country_code | US |
| authorships[10].institutions[2].display_name | Harvard University |
| authorships[10].author_position | middle |
| authorships[10].raw_author_name | Soumya Raychauduri |
| authorships[10].is_corresponding | False |
| authorships[10].raw_affiliation_strings | Center for Data Sciences, Harvard Medical School, Boston, MA, Department of Biomedical Informatics, Harvard Medical School, Boston, MA, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, Divisions of Genetics, Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, Graduate School of Arts and Sciences, Harvard University, Boston, MA |
| authorships[11].author.id | https://openalex.org/A5066797582 |
| authorships[11].author.orcid | https://orcid.org/0000-0002-2971-7975 |
| authorships[11].author.display_name | Alkes L. Price |
| authorships[11].countries | US |
| authorships[11].affiliations[0].institution_ids | https://openalex.org/I107606265 |
| authorships[11].affiliations[0].raw_affiliation_string | Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA |
| authorships[11].affiliations[1].institution_ids | https://openalex.org/I136199984 |
| authorships[11].affiliations[1].raw_affiliation_string | Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[11].affiliations[2].institution_ids | https://openalex.org/I136199984 |
| authorships[11].affiliations[2].raw_affiliation_string | Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA |
| authorships[11].institutions[0].id | https://openalex.org/I107606265 |
| authorships[11].institutions[0].ror | https://ror.org/05a0ya142 |
| authorships[11].institutions[0].type | nonprofit |
| authorships[11].institutions[0].lineage | https://openalex.org/I107606265 |
| authorships[11].institutions[0].country_code | US |
| authorships[11].institutions[0].display_name | Broad Institute |
| authorships[11].institutions[1].id | https://openalex.org/I136199984 |
| authorships[11].institutions[1].ror | https://ror.org/03vek6s52 |
| authorships[11].institutions[1].type | education |
| authorships[11].institutions[1].lineage | https://openalex.org/I136199984 |
| authorships[11].institutions[1].country_code | US |
| authorships[11].institutions[1].display_name | Harvard University |
| authorships[11].author_position | last |
| authorships[11].raw_author_name | Alkes L. Price |
| authorships[11].is_corresponding | False |
| authorships[11].raw_affiliation_strings | Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA |
| has_content.pdf | True |
| has_content.grobid_xml | True |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdf |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Annotations capturing cell-type-specific TF binding explain a large fraction of disease heritability |
| has_fulltext | True |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T10222 |
| primary_topic.field.id | https://openalex.org/fields/13 |
| primary_topic.field.display_name | Biochemistry, Genetics and Molecular Biology |
| primary_topic.score | 0.9993000030517578 |
| primary_topic.domain.id | https://openalex.org/domains/1 |
| primary_topic.domain.display_name | Life Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1312 |
| primary_topic.subfield.display_name | Molecular Biology |
| primary_topic.display_name | Genomics and Chromatin Dynamics |
| related_works | https://openalex.org/W2281560785, https://openalex.org/W3152090159, https://openalex.org/W2258846206, https://openalex.org/W2110808585, https://openalex.org/W2329094632, https://openalex.org/W1994153931, https://openalex.org/W2986565703, https://openalex.org/W45701117, https://openalex.org/W61640353, https://openalex.org/W4322502368 |
| cited_by_count | 6 |
| counts_by_year[0].year | 2024 |
| counts_by_year[0].cited_by_count | 3 |
| counts_by_year[1].year | 2021 |
| counts_by_year[1].cited_by_count | 1 |
| counts_by_year[2].year | 2020 |
| counts_by_year[2].cited_by_count | 1 |
| counts_by_year[3].year | 2019 |
| counts_by_year[3].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.1101/474684 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306402567 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | False |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| best_oa_location.source.host_organization | https://openalex.org/I2750212522 |
| best_oa_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| best_oa_location.license | other-oa |
| best_oa_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdf |
| best_oa_location.version | acceptedVersion |
| best_oa_location.raw_type | posted-content |
| best_oa_location.license_id | https://openalex.org/licenses/other-oa |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | https://doi.org/10.1101/474684 |
| primary_location.id | doi:10.1101/474684 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306402567 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | False |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | bioRxiv (Cold Spring Harbor Laboratory) |
| primary_location.source.host_organization | https://openalex.org/I2750212522 |
| primary_location.source.host_organization_name | Cold Spring Harbor Laboratory |
| primary_location.source.host_organization_lineage | https://openalex.org/I2750212522 |
| primary_location.license | other-oa |
| primary_location.pdf_url | https://www.biorxiv.org/content/biorxiv/early/2018/11/20/474684.full.pdf |
| primary_location.version | acceptedVersion |
| primary_location.raw_type | posted-content |
| primary_location.license_id | https://openalex.org/licenses/other-oa |
| primary_location.is_accepted | True |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | https://doi.org/10.1101/474684 |
| publication_date | 2018-11-20 |
| publication_year | 2018 |
| referenced_works | https://openalex.org/W2117446594, https://openalex.org/W2078059415, https://openalex.org/W2133009026, https://openalex.org/W2163353298, https://openalex.org/W2785792383, https://openalex.org/W2152406028, https://openalex.org/W1995716639, https://openalex.org/W2029530775, https://openalex.org/W2273953524, https://openalex.org/W2148853260, https://openalex.org/W2295392542, https://openalex.org/W2757552016, https://openalex.org/W2023798198, https://openalex.org/W2259938310, https://openalex.org/W1979521131, https://openalex.org/W1988393300, https://openalex.org/W2084620487, https://openalex.org/W1900337607, https://openalex.org/W2146042781, https://openalex.org/W2112484474, https://openalex.org/W2033169664, https://openalex.org/W2212528563, https://openalex.org/W2198606573, https://openalex.org/W1019830208, https://openalex.org/W2433743436, https://openalex.org/W2345512687, https://openalex.org/W2951544440, https://openalex.org/W2142410561, https://openalex.org/W2278401009, https://openalex.org/W2019251848, https://openalex.org/W1844405070, https://openalex.org/W2952882474, https://openalex.org/W2018363492, https://openalex.org/W2159324718, https://openalex.org/W1887067757, https://openalex.org/W2123861597, https://openalex.org/W2953357410, https://openalex.org/W2892391774, https://openalex.org/W2101505979, https://openalex.org/W2522774247, https://openalex.org/W2152325859, https://openalex.org/W2259892741, https://openalex.org/W2949697961, https://openalex.org/W2571173152, https://openalex.org/W2949754140, https://openalex.org/W2884616392, https://openalex.org/W2617742891, https://openalex.org/W1983539381, https://openalex.org/W2188707104, https://openalex.org/W2791532151, https://openalex.org/W3100332947, https://openalex.org/W2809388509 |
| referenced_works_count | 52 |
| abstract_inverted_index.8 | 192 |
| abstract_inverted_index.9 | 170 |
| abstract_inverted_index.= | 169, 191 |
| abstract_inverted_index.P | 168 |
| abstract_inverted_index.a | 9, 140, 177 |
| abstract_inverted_index.(P | 190 |
| abstract_inverted_index.10 | 172, 194 |
| abstract_inverted_index.49 | 107 |
| abstract_inverted_index.It | 1 |
| abstract_inverted_index.LD | 116 |
| abstract_inverted_index.TF | 34, 49, 55, 97, 135, 204 |
| abstract_inverted_index.We | 91, 127 |
| abstract_inverted_index.an | 153 |
| abstract_inverted_index.be | 72 |
| abstract_inverted_index.by | 52, 102 |
| abstract_inverted_index.in | 12, 156, 180 |
| abstract_inverted_index.is | 2, 23, 124 |
| abstract_inverted_index.of | 19, 95, 106, 142 |
| abstract_inverted_index.on | 77, 184 |
| abstract_inverted_index.or | 74 |
| abstract_inverted_index.to | 25, 160 |
| abstract_inverted_index.vs | 166 |
| abstract_inverted_index.we | 46 |
| abstract_inverted_index.× | 171, 193 |
| abstract_inverted_index.-11 | 195 |
| abstract_inverted_index.-14 | 173 |
| abstract_inverted_index.12% | 178 |
| abstract_inverted_index.58% | 154 |
| abstract_inverted_index.Our | 198 |
| abstract_inverted_index.and | 15, 81, 99, 109, 176 |
| abstract_inverted_index.are | 37, 87 |
| abstract_inverted_index.but | 28 |
| abstract_inverted_index.can | 210 |
| abstract_inverted_index.for | 41, 174, 196 |
| abstract_inverted_index.may | 71 |
| abstract_inverted_index.not | 38, 89, 125 |
| abstract_inverted_index.six | 143 |
| abstract_inverted_index.the | 66, 82, 104, 120, 161, 187 |
| abstract_inverted_index.(TF) | 22 |
| abstract_inverted_index.both | 65 |
| abstract_inverted_index.data | 101 |
| abstract_inverted_index.from | 31, 186 |
| abstract_inverted_index.gene | 26 |
| abstract_inverted_index.help | 211 |
| abstract_inverted_index.most | 42 |
| abstract_inverted_index.role | 11 |
| abstract_inverted_index.show | 200 |
| abstract_inverted_index.that | 5, 16, 68, 84, 129, 201 |
| abstract_inverted_index.this | 62 |
| abstract_inverted_index.with | 58, 119, 139, 152, 206 |
| abstract_inverted_index.100bp | 130 |
| abstract_inverted_index.7.3x; | 167 |
| abstract_inverted_index.Here, | 45 |
| abstract_inverted_index.alone | 164 |
| abstract_inverted_index.best, | 151 |
| abstract_inverted_index.bound | 73 |
| abstract_inverted_index.data; | 61 |
| abstract_inverted_index.known | 4 |
| abstract_inverted_index.major | 10 |
| abstract_inverted_index.marks | 146, 163 |
| abstract_inverted_index.model | 122, 189 |
| abstract_inverted_index.plays | 8 |
| abstract_inverted_index.score | 117 |
| abstract_inverted_index.union | 141 |
| abstract_inverted_index.using | 114, 148 |
| abstract_inverted_index.(11.6x | 165 |
| abstract_inverted_index.(which | 123 |
| abstract_inverted_index.around | 132 |
| abstract_inverted_index.pairs. | 44 |
| abstract_inverted_index.refine | 212 |
| abstract_inverted_index.signal | 182 |
| abstract_inverted_index.traits | 111 |
| abstract_inverted_index.widely | 3 |
| abstract_inverted_index.N=320K) | 113 |
| abstract_inverted_index.binding | 18, 35, 50, 56, 136 |
| abstract_inverted_index.complex | 13, 110 |
| abstract_inverted_index.disease | 14 |
| abstract_inverted_index.factors | 21 |
| abstract_inverted_index.genomic | 29 |
| abstract_inverted_index.results | 199 |
| abstract_inverted_index.unbound | 75 |
| abstract_inverted_index.windows | 131 |
| abstract_inverted_index.(average | 112 |
| abstract_inverted_index.(imputed | 147 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.MotifMap | 133 |
| abstract_inverted_index.compared | 159 |
| abstract_inverted_index.context, | 80 |
| abstract_inverted_index.critical | 24 |
| abstract_inverted_index.directly | 32 |
| abstract_inverted_index.diseases | 108 |
| abstract_inverted_index.increase | 155, 179 |
| abstract_inverted_index.measured | 33 |
| abstract_inverted_index.signals. | 215 |
| abstract_inverted_index.strategy | 63 |
| abstract_inverted_index.addresses | 64 |
| abstract_inverted_index.available | 40 |
| abstract_inverted_index.chromatin | 60, 79, 100, 145, 162, 208 |
| abstract_inverted_index.construct | 47 |
| abstract_inverted_index.currently | 39 |
| abstract_inverted_index.depending | 76 |
| abstract_inverted_index.different | 93 |
| abstract_inverted_index.evaluated | 92 |
| abstract_inverted_index.generally | 88 |
| abstract_inverted_index.identical | 69 |
| abstract_inverted_index.performed | 150 |
| abstract_inverted_index.sequences | 70 |
| abstract_inverted_index.variation | 7 |
| abstract_inverted_index.determined | 128 |
| abstract_inverted_index.enrichment | 158 |
| abstract_inverted_index.limitation | 67, 83 |
| abstract_inverted_index.regression | 118 |
| abstract_inverted_index.regulatory | 6 |
| abstract_inverted_index.stratified | 115 |
| abstract_inverted_index.annotations | 30, 51, 185 |
| abstract_inverted_index.association | 214 |
| abstract_inverted_index.baseline-LD | 121, 188 |
| abstract_inverted_index.conditional | 183 |
| abstract_inverted_index.difference) | 175 |
| abstract_inverted_index.genome-wide | 213 |
| abstract_inverted_index.information | 36, 209 |
| abstract_inverted_index.intersected | 138 |
| abstract_inverted_index.predictions | 57, 86, 98, 137, 205 |
| abstract_inverted_index.regulation, | 27 |
| abstract_inverted_index.surrounding | 78 |
| abstract_inverted_index.ChromImpute) | 149 |
| abstract_inverted_index.cell-type-TF | 43 |
| abstract_inverted_index.combinations | 94 |
| abstract_inverted_index.difference). | 197 |
| abstract_inverted_index.heritability | 105, 157 |
| abstract_inverted_index.intersecting | 53, 202 |
| abstract_inverted_index.partitioning | 103 |
| abstract_inverted_index.transcription | 20 |
| abstract_inverted_index.sequence-based | 54, 85, 96, 203 |
| abstract_inverted_index.sequenced-based | 134 |
| abstract_inverted_index.cell-type-specific | 17, 48, 59, 144, 181, 207 |
| abstract_inverted_index.cell-type-specific. | 90 |
| abstract_inverted_index.cell-type-specific). | 126 |
| cited_by_percentile_year.max | 97 |
| cited_by_percentile_year.min | 89 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 12 |
| citation_normalized_percentile.value | 0.58468645 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |