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LOGIQA: a database dedicated to long-range genome interactions quality assessment.
Mendoza-Parra, Marco-Antonio; Blum, Matthias; Malysheva, Valeriya; Cholley, Pierre-Etienne; Gronemeyer, Hinrich.
Affiliation
  • Mendoza-Parra MA; Equipe Labellisée Ligue Contre le Cancer, Illkirch, France. marco@igbmc.fr.
  • Blum M; Department of Functional Genomics and Cancer, Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Illkirch, France. marco@igbmc.fr.
  • Malysheva V; Centre National de la Recherche Scientifique UMR 7104, Illkirch, France. marco@igbmc.fr.
  • Cholley PE; Institut National de la Santé et de la Recherche Médicale U964, Illkirch, France. marco@igbmc.fr.
  • Gronemeyer H; University of Strasbourg, Illkirch, France. marco@igbmc.fr.
BMC Genomics ; 17: 355, 2016 05 16.
Article in En | MEDLINE | ID: mdl-27185059
ABSTRACT

BACKGROUND:

Proximity ligation-mediated methods are essential to study the impact of three-dimensional chromatin organization on gene programming. Albeit significant progress has been made in the development of computational tools that assess long-range chromatin interactions, next to nothing is known about the quality of the generated datasets.

METHOD:

We have developed LOGIQA ( www.ngs-qc.org/logiqa ), a database hosting quality scores for long-range genome interaction assays, accessible through a user-friendly web-based environment.

RESULTS:

Currently, LOGIQA harbors QC scores for >900 datasets, which provides a global view of their relative quality and reveals the impact of genome size, coverage and other technical aspects. LOGIQA provides a user-friendly dataset query panel and a genome viewer to assess local genome-interaction maps at different resolution and quality-assessment conditions.

CONCLUSIONS:

LOGIQA is the first database hosting quality scores dedicated to long-range chromatin interaction assays, which in addition provides a platform for visualizing genome interactions made available by the scientific community.
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Full text: 1 Database: MEDLINE Main subject: Software / Genome / Genomics / Databases, Genetic Language: En Year: 2016 Type: Article

Full text: 1 Database: MEDLINE Main subject: Software / Genome / Genomics / Databases, Genetic Language: En Year: 2016 Type: Article