Motif-Raptor: a cell type-specific and transcription factor centric approach for post-GWAS prioritization of causal regulators Article Swipe
Qiuming Yao
,
Paolo Ferragina
,
Yakir Reshef
,
Guillaume Lettre
,
Daniel E. Bauer
,
Luca Pinello
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/btab072
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/btab072
Motivation Genome-wide association studies (GWASs) have identified thousands of common trait-associated genetic variants but interpretation of their function remains challenging. These genetic variants can overlap the binding sites of transcription factors (TFs) and therefore could alter gene expression. However, we currently lack a systematic understanding on how this mechanism contributes to phenotype. Results We present Motif-Raptor, a TF-centric computational tool that integrates sequence-based predictive models, chromatin accessibility, gene expression datasets and GWAS summary statistics to systematically investigate how TF function is affected by genetic variants. Given trait-associated non-coding variants, Motif-Raptor can recover relevant cell types and critical TFs to drive hypotheses regarding their mechanism of action. We tested Motif-Raptor on complex traits such as rheumatoid arthritis and red blood cell count and demonstrated its ability to prioritize relevant cell types, potential regulatory TFs and non-coding SNPs which have been previously characterized and validated. Availability and implementation Motif-Raptor is freely available as a Python package at: https://github.com/pinellolab/MotifRaptor. Supplementary information Supplementary data are available at Bioinformatics online.
Related Topics
Concepts
Computational biology
Genome-wide association study
Chromatin
Biology
Transcription factor
Gene
Genetics
Single-nucleotide polymorphism
Genotype
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/bioinformatics/btab072
- OA Status
- green
- Cited By
- 9
- References
- 76
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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- DOI
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https://doi.org/10.1093/bioinformatics/btab072Digital Object Identifier
- Title
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Motif-Raptor: a cell type-specific and transcription factor centric approach for post-GWAS prioritization of causal regulatorsWork title
- Type
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articleOpenAlex work type
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enPrimary language
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2021Year of publication
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2021-01-28Full publication date if available
- Authors
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Qiuming Yao, Paolo Ferragina, Yakir Reshef, Guillaume Lettre, Daniel E. Bauer, Luca PinelloList of authors in order
- Landing page
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https://doi.org/10.1093/bioinformatics/btab072Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://hdl.handle.net/11568/1115388Direct OA link when available
- Concepts
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Computational biology, Genome-wide association study, Chromatin, Biology, Transcription factor, Gene, Genetics, Single-nucleotide polymorphism, GenotypeTop concepts (fields/topics) attached by OpenAlex
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9Total citation count in OpenAlex
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2025: 1, 2024: 2, 2023: 5, 2021: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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