GeneNetwork: framework for web-based genetics
Open accessAbstract
GeneNetwork (GN) is a free and open source (FOSS) framework for web-based genetics that can be deployed anywhere. GN allows biologists to upload high-throughput experimental data, such as expression data from microarrays and RNA-seq, and also `classic' phenotypes, such as disease phenotypes. These phenotypes can be mapped interactively against genotypes using embedded tools, such as R/QTL (Arends et al. 2010) mapping, interval mapping for model organisms and pylmm; an implementation of FaST-LMM (Lippert et al. 2011) which is more suitable for human populations and outbred crosses, such as the mouse diversity outcross. Interactive D3 graphics are included from R/qtlcharts and presentation-ready figures can be generated. Recently we have added functionality for phenotype correlation (Wang et al. 2016) and network analysis (Langfelder and Horvath 2008).
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Densities of aβ plaques and NeuN+ cells can be estimated in anatomically corrected stereotaxic space using a digital version of direct 3-dimensional counting (optical disector).
“We can estimate densities of aβ plaques and NeuN+ cells in anatomically corrected stereotaxic space using a digital version of direct 3-dimensional counting, now often referred to as the optical disector23,99.”
From Magnetic resonance microscopy maps widespread effects of Alzheimer’s disease on brain structures and behavior in mice (2026) · cites this paper as [99]
The main GeneNetwork section describes web-based genetic mapping and analysis, not anatomical cell or plaque counting. Searches for optical disector, NeuN, amyloid plaques, stereotaxic space, and digital stereology found no passage addressing the claimed method; the copy provides neither support nor a contrary finding. (LLM, conf=0.75)
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References 4 · Cited by 37
Research works printed but not linked: 5
- Arends, D., P. Prins, R. C. Jansen, and K. W. Broman. 2010. "R/qtl: high-throughput multiple QTL mapping." Bioinformatics 26 (23): 2990-2. doi:10.1093/bioinformatics/btq565. · DOI
- Langfelder, P., and S. Horvath. 2008. "WGCNA: an R package for weighted correlation network analysis." BMC Bioinformatics 9: 559. doi:10.1186/1471-2105-9-559. · DOI · Paper page
- Lippert, C., J. Listgarten, Y. Liu, C. M. Kadie, R. I. Davidson, and D. Heckerman. 2011. "FaST linear mixed models for genome-wide association studies." Nat Methods 8 (10): 833-35. doi:10.1038/nmeth.1681. · DOI · Paper page
- Wang, X., A. K. Pandey, M. K. Mulligan, E. G. Williams, K. Mozhui, Z. Li, V. Jovaisaite, et al. 2016. "Joint mouse-human phenome-wide association to test gene function and disease risk." Nat Commun 7: 10464. doi:10.1038/ncomms10464. · DOI
- Sloan et al., (2016). GeneNetwork: framework for web-based genetics. Journal of Open Source Software, 1(2), 25, doi:10.21105/joss.00025
- Authors
- Sloan, Z., Arends, D., W. Broman, K., Centeno, A., Furlotte, N., Nijveen, H., Yan, L., Zhou, X., W. Williams, R., & Prins, P.
- Affiliations
- University of Tennessee Health Science Center (US)
- Humboldt-Universität zu Berlin (DE)
- Wageningen University & Research (NL)
- University of Michigan (US)
- ORCID
- Venue
- The Journal of Open Source Software
- Publisher
- The Open Journal
- Published
- 2016-06-17
- Volume
- 1
- Issue
- 2
- Pages
- 25
- ISSN
- 2475-9066 (ISSN-L)
- OpenAlex
- W2442033574
- Cited by
- 37
- References
- 4
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 2 · 2023: 4 · 2022: 1 · 2021: 7 · 2020: 3 · 2019: 4 · 2018: 3 · 2016: 1
- Type
- software paper
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- Locations
- The Journal of Open Source Software (publishedVersion, cc-by)
- Socio-Environmental Systems Modeling (acceptedVersion, cc-by)
- Data Archiving and Networked Services (DANS) (submittedVersion, cc-by)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- genome-wide association study, QTL mapping, interval mapping, phenotypic correlation, gene expression data, microarray, RNA-seq, disease phenotypes, network analysis, outbred populations, open source software
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