TY  - JOUR
A1  - Ball, Robyn L.
A1  - Bogue, Molly A.
A1  - Liang, Hongping
A1  - Srivastava, Anuj
A1  - Ashbrook, David G.
A1  - Lamoureux, Anna
A1  - Gerring, Matthew W.
A1  - Hatoum, Alexander S.
A1  - Kim, Matthew J.
A1  - He, Hao
A1  - Emerson, Jake
A1  - Berger, Alexander K.
A1  - Walton, David O.
A1  - Sheppard, Keith
A1  - El Kassaby, Baha
A1  - Castellanos, Francisco
A1  - Kunde-Ramamoorthy, Govindarajan
A1  - Lu, Lu
A1  - Bluis, John
A1  - Desai, 
Sejal
A1  - Sundberg, Beth A.
A1  - Peltz, Gary
A1  - Fang, Zhuoqing
A1  - Churchill, Gary A.
A1  - Williams, Robert W.
A1  - Agrawal, Arpana
A1  - Bult, Carol J.
A1  - Philip, Vivek M.
A1  - Chesler, Elissa J.
T1  - GenomeMUSter mouse genetic variation service enables multitrait, multipopulation data integration and analysis
Y1  - 2024/01/01 
JF  - Genome Research 
JO  - Genome Research 
SP  - 145 
EP  - 159 
DO  - 10.1101/gr.278157.123 
VL  - 34 
IS  - 1 
UR  - http://genome.cshlp.org/content/34/1/145.abstract 
N2  - Hundreds of inbred mouse strains and intercross populations have been used to characterize the function of genetic variants that contribute to disease. Thousands of disease-relevant traits have been characterized in mice and made publicly available. New strains and populations including consomics, the collaborative cross, expanded BXD, and inbred wild-derived strains add to existing complex disease mouse models, mapping populations, and sensitized backgrounds for engineered mutations. The genome sequences of inbred strains, along with dense genotypes from others, enable integrated analysis of trait–variant associations across populations, but these analyses are hampered by the sparsity of genotypes available. Moreover, the data are not readily interoperable with other resources. To address these limitations, we created a uniformly dense variant resource by harmonizing multiple data sets. Missing genotypes were imputed using the Viterbi algorithm with a data-driven technique that incorporates local phylogenetic information, an approach that is extendable to other model organisms. The result is a web- and programmatically accessible data service called GenomeMUSter, comprising single-nucleotide variants covering 657 strains at 106.8 million segregating sites. Interoperation with phenotype databases, analytic tools, and other resources enable a wealth of applications, including 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 of strain backgrounds for disease modeling to further unlock extant mouse diversity for genetic and genomic studies in health and disease. 
ER  -