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Resource: GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis
- Robyn L. Ball,
- Molly A. Bogue,
- Hongping Liang,
- Anuj Srivastava,
- David G. Ashbrook,
- Anna Lamoureux,
- Matthew W. Gerring,
- Alexander S. Hatoum,
- Matthew J. Kim,
- Hao He,
- Jake Emerson,
- Alexander K. Berger,
- David O. Walton,
- Keith Sheppard,
- Baha El Kassaby,
- Francisco Castellanos,
- Govindarajan Kunde-Ramamoorthy,
- Lu Lu,
- John Bluis,
- Sejal Desai,
- Beth A. Sundberg,
- Gary Peltz,
- Zhuoqing Fang,
- Gary A. Churchill,
- Robert W. Williams,
- Arpana Agrawal,
- Carol J. Bult,
- Vivek M. Philip,
- and Elissa J. Chesler
Genome Res. January 2024 34: 145-159; Published in Advance January 30, 2024, doi:10.1101/gr.278157.123
...multitrait, multipopulation meta-analysis. We show this in cross-species comparisons of type 2 diabetes and substance use disorder meta-analyses, leveraging mouse data to characterize the likely role of human variant effects in disease. Other applications include refinement of mapped loci and prioritization...
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Resource: Global compositional and functional states of the human gut microbiome in health and disease
- Sunjae Lee,
- Theo Portlock,
- Emmanuelle Le Chatelier,
- Fernando Garcia-Guevara,
- Frederick Clasen,
- Florian Plaza Oñate,
- Nicolas Pons,
- Neelu Begum,
- Azadeh Harzandi,
- Ceri Proffitt,
- Dorines Rosario,
- Stefania Vaga,
- Junseok Park,
- Kalle von Feilitzen,
- Fredric Johansson,
- Cheng Zhang,
- Lindsey A. Edwards,
- Vincent Lombard,
- Franck Gauthier,
- Claire J. Steves,
- David Gomez-Cabrero,
- Bernard Henrissat,
- Doheon Lee,
- Lars Engstrand,
- Debbie L. Shawcross,
- Gordon Proctor,
- Mathieu Almeida,
- Jens Nielsen,
- Adil Mardinoglu,
- David L. Moyes,
- Stanislav Dusko Ehrlich,
- Mathias Uhlen,
- and Saeed Shoaie
Genome Res. June 2024 34: 967-978; Published in Advance July 22, 2024, doi:10.1101/gr.278637.123
...from both healthy and diseased individuals. To overcome the current limitations of meta-analyses of microbiome studies, we used a machine learning approach to extract microbial features from different diseases. We calculated the enrichment of microbial species for both disease and geographical regions...
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Method: Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes
- George Armstrong,
- Kalen Cantrell,
- Shi Huang,
- Daniel McDonald,
- Niina Haiminen,
- Anna Paola Carrieri,
- Qiyun Zhu,
- Antonio Gonzalez,
- Imran McGrath,
- Kristen L. Beck,
- Daniel Hakim,
- Aki S. Havulinna,
- Guillaume Méric,
- Teemu Niiranen,
- Leo Lahti,
- Veikko Salomaa,
- Mohit Jain,
- Michael Inouye,
- Austin D. Swafford,
- Ho-Cheol Kim,
- Laxmi Parida,
- Yoshiki Vázquez-Baeza,
- and Rob Knight
Genome Res. November 2021 31: 2131-2137; Published in Advance September 3, 2021, doi:10.1101/gr.275777.121
...in the phylogenetic tree, as well as the number of samples in the underlying data table.In today's increasingly large and sparse data sets and meta-analyses, these phylogenetic trees and tables can exceed hundreds of thousands of samples and millions of tree tips (McDonald et al. 2018b). Recent advances have enabled...

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