Author

Danilo Horta

European Bioinformatics InstituteORCID 0000-0003-4832-2124Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Genetics· 2 Bioinformatics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Research Focus:gene regulatory network inference· 4 Organism:human· 4 Approach:statistical model· 4 Research Focus:GWAS / association mapping· 3 Assay:GWAS summary statistics· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Research Focus:differential expression· 1

Frequent Co-Authors

Oliver StegleiD· 4 shared Francesco Paolo CasaleiD· 2 shared Marc Jan BonderiD· 2 shared Anna S. E. CuomoiD· 1 shared Barbara Rakitsch· 1 shared Bogdan Andrei MirautaiD· 1 shared Christopher D. BrowniD· 1 shared Chunli ZhaoiD· 1 shared

Activity by Year

2017-2022 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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4 shared papersGenetics

Oliver StegleORCID

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4 papers

Recent·Most cited

CellRegMap: A statistical framework for mapping context-specific regulatory variants using scRNA-seq

Anna S. E. Cuomo, Tobias Heinen, Danai Vagiaki, Danilo Horta, John C. Marioni, Oliver Stegle

CellRegMap identifies context-specific regulatory variants using scRNA-seq by analyzing allelic effects across cell types and states.

Molecular Systems Biology · Aug 1, 2022Peer-reviewedBioinformatics

Systematic assessment of regulatory effects of human disease variants in pluripotent cells

Marc Jan Bonder, Craig Smail, Michael J. Gloudemans, Laure Frésard, David A. Jakubosky, Matteo D’Antonio, Xin Li, Nicole M. Ferraro, Ivan Carcamo‐Orive, Bogdan Andrei Mirauta, Daniel D. Seaton, Na Cai, Dara Vakili, Danilo Horta, Chunli Zhao, , Oliver Stegle

The paper maps regulatory effects of human disease variants in pluripotent cells, identifying cis- and trans-QTL across 18,556 genes and linking them to GWAS traits.

Nature Genetics · Mar 1, 2021Peer-reviewedGenomics

A linear mixed model approach to study multivariate gene-environment interactions

Rachel Moore, Francesco Paolo Casale, Marc Jan Bonder, Danilo Horta, Lude Franke, Inês Barroso, Oliver Stegle

This paper introduces StructLMM, a linear mixed model for analyzing multivariate gene-environment interactions, demonstrating its effectiveness in detecting GxE signals in BMI and eQTL data.

Nature Genetics · Nov 21, 2018Peer-reviewedGenetics

Joint genetic analysis using variant sets reveals polygenic gene-context interactions

Francesco Paolo Casale, Danilo Horta, Barbara Rakitsch, Oliver Stegle

The paper introduces iSet, a method for detecting gene-context interactions using linear mixed models, and finds it identifies more interactions than alternative methods, including a gene-sex interaction for C-reactive protein.

PLoS Genetics · Apr 20, 2017Peer-reviewedGenetics