LOGIQA

LOGIQA evaluates the quality of long-range genome interaction assays from proximity ligation-mediated methods to provide quantitative quality scores that inform analyses of three-dimensional chromatin organization and its impact on gene regulation.


Key Features:

  • Quality Scoring System: Assigns quantitative quality scores to long-range genome interaction datasets to enable comparative evaluation of dataset integrity.
  • Dataset Scope: Contains quality assessments for over 900 long-range genome interaction datasets.
  • Technical Parameter Analysis: Evaluates the impact of technical parameters such as genome size and coverage depth on dataset quality.
  • Genome Interaction Visualization: Provides visualization of local genome-interaction maps at varying resolutions and under different quality-assessment conditions.
  • Proximity Ligation–Method Assessment: Implements an assessment framework specific to proximity ligation-mediated long-range chromatin interaction assays.

Scientific Applications:

  • Chromatin architecture studies: Supports analysis of three-dimensional genome organization and chromatin architecture.
  • Gene regulation research: Informs investigations into the impact of genome interactions on gene regulation.
  • Epigenetics: Aids studies of epigenetic modifications that are associated with long-range chromatin interactions.
  • Dataset selection and benchmarking: Facilitates selection of high-quality datasets and benchmarking of experimental and computational protocols.

Methodology:

Uses computational assessment methods that integrate coverage depth and genome size to systematically evaluate long-range chromatin interaction data and highlight potential biases or errors within datasets.

Topics

Details

Tool Type:
web application
Operating Systems:
Linux, Windows, Mac
Added:
5/19/2018
Last Updated:
12/10/2018

Operations

Publications

Mendoza-Parra M, Blum M, Malysheva V, Cholley P, Gronemeyer H. LOGIQA: a database dedicated to long-range genome interactions quality assessment. BMC Genomics. 2016;17(1). doi:10.1186/s12864-016-2642-1. PMID:27185059. PMCID:PMC4868109.

Documentation