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Leveraging eQTLs to identify individual-level tissue of interest for a complex trait

PLoS Computational Biology(2021)10.1371/journal.pcbi.1008915Source: DataRank Database

Leveraging eQTLs to identify individual-level tissue of interest for a complex trait is a research paper published in PLoS Computational Biology (2021). On theSindex it has a DataRank of 0.269. It has been cited 5 times.

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0.269DataRank · unranked

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Open Access5 citations

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datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (19 grants)OA: goldTopics (61)IDs (PubMed, PMC)SDGs (2)

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Findable (1/2)

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Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

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DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.269

From this paper's citation signal

Citation Network Contribution

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Authors (8)

Claudia Giambartolomei ORCID,Na Cai ORCID,Tanushree Haldar ORCID,Tommer Schwarz ORCID,Michael J. Gandal ORCID

Live enrichment

PubMed:34019542 PMC:PMC8174686

National Institutes of Health

Grant: T32MH073526

National Institutes of Health

Grant: T32NS048004

NCI NIH HHS

Grant: U01 CA194393

NHGRI NIH HHS

Grant: R01 HG009120

National Institutes of Health

Grant: R01MH115676

NHGRI NIH HHS

Grant: T32 HG002536

NIMH NIH HHS

Grant: R37 MH085953

NCI NIH HHS

Grant: R01 CA194393

NHGRI NIH HHS

Grant: R01 HG006399

NIMH NIH HHS

Grant: R01 MH121521

Medical Research Council

Grant: MC_QA137853

Medical Research Council

Grant: MC_PC_17228

National Institutes of Health

Grant: 3T32HG002536-06S1

Training Grant in Genomic Analysis and Interpretation

National Institutes of Health

Grant: 2T32MH073526-06

Training Grant in Neurobehavioral Genetics

National Institutes of Health

Grant: 2R01HG006399-10A1

Leveraging functional data to predict disease risk in multi-ethnic populations

National Institutes of Health

Grant: 5R01HG009120-04

Integrative approaches for mapping the genetic risk of complex traits

National Institutes of Health

Grant: 5R01MH115676-08

Integrating case-control transcriptomic and genetic data in admixed individuals to identify disease genes for schizophrenia and bipolar disorder

National Institutes of Health

Grant: 3T32NS048004-06A1S1

Training Grant in Neurobehavioral Genetics

National Institutes of Health

Grant: 5U01CA194393-04

Quantifying and Characterizing the shared genetic contribution to common cancers

goldLicense: cc-by

publisherhttps://doi.org/10.1371/journal.pcbi.1008915

repositoryhttps://doaj.org/article/c1c77a8e2ad24712b5cb0d0acb5429fc

repositoryhttps://escholarship.org/uc/item/2bz155vz

repositoryhttps://www.ncbi.nlm.nih.gov/pmc/articles/8174686

Europe_PMChttps://europepmc.org/articles/PMC8174686

Fields of Study

0301 basic medicine03 medical and health sciences

MeSH Terms

BrainAdipose TissueHumansObesityGenetic Predisposition to DiseaseBody Mass IndexBayes TheoremComputational BiologyOrgan SpecificityGene ExpressionTissue DistributionMultifactorial InheritancePhenotypePolymorphism, Single NucleotideQuantitative Trait LociAlgorithmsModels, GeneticComputer SimulationSoftware

Keywords

Multifactorial InheritanceEpidemiologyBioinformaticsQH301-705.5Quantitative Trait Loci610Gene ExpressionCardiovascularPolymorphism, Single NucleotideMathematical Sciences576Body Mass IndexGeneticModelsInformation and Computing SciencesHealth SciencesGenetics2.1 Biological and endogenous factorsHumansComputer SimulationGenetic Predisposition to DiseaseTissue DistributionObesityPolymorphismBiology (General)NutritionModels, GeneticHuman GenomeBrainComputational BiologyBayes TheoremSingle NucleotideBiological Sciences4.1 Discovery and preclinical testing of markers and technologiesPhenotypeAdipose TissueOrgan SpecificityAlgorithmsSoftwareResearch Article

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