diff --git a/CITATION.cff b/CITATION.cff new file mode 100644 index 0000000000000000000000000000000000000000..9ed5f18cf36de7baa86ab083450a96026853a13e --- /dev/null +++ b/CITATION.cff @@ -0,0 +1,90 @@ +# This CITATION.cff file was generated with cffinit. +# Visit https://bit.ly/cffinit to generate yours today! + +cff-version: 1.2.0 +title: CCQTL +message: >- + If you use this software, please cite it using the + metadata from this file. +type: software +authors: + - given-names: Remi + family-names: Planel + email: remi.planel@pasteur.fr + affiliation: >- + Université Paris Cité, Bioinformatics and + Biostatistics Hub, F-75015 Paris, France + orcid: 'https://orcid.org/0000-0002-7826-3316' + - given-names: Victoire + family-names: Baillet + email: victoire.baillet@pasteur.fr + affiliation: >- + Institut Pasteur, Université Paris Cité, + Bioinformatics and Biostatistics Hub, F-75015 Paris, + France + orcid: 'https://orcid.org/0000-0002-1081-2921' + - given-names: Vincent + family-names: Guillemot + orcid: 'https://orcid.org/0000-0002-7421-0655' + email: vincent.guillemot@pasteur.fr + affiliation: >- + Institut Pasteur, Université Paris Cité, + Bioinformatics and Biostatistics Hub, F-75015 Paris, + France + - given-names: Pascal + family-names: Campagne + email: pascal.campagne@pasteur.fr + affiliation: >- + Institut Pasteur, Université Paris Cité, + Bioinformatics and Biostatistics Hub, F-75015 Paris, + France + orcid: 'https://orcid.org/0000-0001-7018-1896' +identifiers: + - type: swh + value: 'swh:1:dir:2acedd6f278157b5b0112245f0febc23a45937ef' + description: >- + Software Heritage identifier for version 1.0.0 of the + work. +repository-code: 'https://gitlab.pasteur.fr/cc-qtl/cc-qtl-db' +abstract: >- + Quantitative Trait Locus (QTL) mapping in mapping + populations and Genome-Wide Association Studies (GWAS) in + natural populations are complementary approaches for + dissecting the genetic architecture of complex traits. + While GWAS are typically carried out by statistical + genetics groups well-versed in quantitative environments + and code management, experimental geneticists performing + QTL mapping focus on labor-intensive phenotyping + experiments thus requiring further support, both for code + and statistics, to benefit from best practices in the + field. + + We present CCQTL, a comprehensive platform for QTL mapping + in the Collaborative Cross (CC), an increasingly used + mouse mapping population. CCQTL features an intuitive + graphical user interface (GUI) for seamless end-to-end QTL + mapping analysis, from data transformation to candidate + gene identification. It also includes a robust database + structure ensuring secure, organized storage of phenotypic + data, accompanied by an advanced permissions system. + + CCQTL's analytical component leverages R/qtl2 tools + integrated into preconfigured Galaxy workflows designed + explicitly for the CC. This setup facilitates one-click, + reproducible analyses. The platform's interface (GUI, + database, and analytics) is containerized using Docker, + enabling straightforward deployment and scalability. While + primarily designed to empower non-specialists in + conducting their own data analyses, CCQTL's Galaxy-brought + reproducibility and sophisticated database permission + system also renders it valuable for experienced users + seeking streamlined solutions. +keywords: + - QTL mapping + - Collaborative Cross + - Web interface + - Database + - Galaxy +license: GPL-3.0 +version: 1.0.0 +date-released: '2023-07-07'