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. 2017 Apr 4;18(1):200.
doi: 10.1186/s12859-017-1612-1.

AHCODA-DB: A Data Repository With Web-Based Mining Tools for the Analysis of Automated High-Content Mouse Phenomics Data

Free PMC article

AHCODA-DB: A Data Repository With Web-Based Mining Tools for the Analysis of Automated High-Content Mouse Phenomics Data

Bastijn Koopmans et al. BMC Bioinformatics. .
Free PMC article


Background: Systematic, standardized and in-depth phenotyping and data analyses of rodent behaviour empowers gene-function studies, drug testing and therapy design. However, no data repositories are currently available for standardized quality control, data analysis and mining at the resolution of individual mice.

Description: Here, we present AHCODA-DB, a public data repository with standardized quality control and exclusion criteria aimed to enhance robustness of data, enabled with web-based mining tools for the analysis of individually and group-wise collected mouse phenotypic data. AHCODA-DB allows monitoring in vivo effects of compounds collected from conventional behavioural tests and from automated home-cage experiments assessing spontaneous behaviour, anxiety and cognition without human interference. AHCODA-DB includes such data from mutant mice (transgenics, knock-out, knock-in), (recombinant) inbred strains, and compound effects in wildtype mice and disease models. AHCODA-DB provides real time statistical analyses with single mouse resolution and versatile suite of data presentation tools. On March 9th, 2017 AHCODA-DB contained 650 k data points on 2419 parameters from 1563 mice.

Conclusion: AHCODA-DB provides users with tools to systematically explore mouse behavioural data, both with positive and negative outcome, published and unpublished, across time and experiments with single mouse resolution. The standardized (automated) experimental settings and the large current dataset (1563 mice) in AHCODA-DB provide a unique framework for the interpretation of behavioural data and drug effects. The use of common ontologies allows data export to other databases such as the Mouse Phenome Database. Unbiased presentation of positive and negative data obtained under the highly standardized screening conditions increase cost efficiency of publicly funded mouse screening projects and help to reach consensus conclusions on drug responses and mouse behavioural phenotypes. The website is publicly accessible through and can be viewed in every recent version of all commonly used browsers.

Keywords: AHCODA; Data analysis; Database; Mouse behaviour; Neuroscience; Phenotyping; Statistics; Visualization.


Fig. 1
Fig. 1
Schematic overview of the workflow underlying the AHCODA-DB repository and website. After data of conventional behavioural tests and automated home-cages is acquired (a), the data are transferred to a MySQL database that includes metadata on mice, behavioural tests and analysis parameters (b). Data is processed by R-scripts (c) selected from user instructions in the AHCODA-DB website interface (d). Results of group comparisons are shown in the web browser as publishable ready art and statistics (e-f) that can be downloaded as a PDF or CSV file (g). The heat map function allows large-scale group comparisons (h)

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