Inbred Strain Variant Database (ISVdb): A repository for probabilistically informed sequence differences among the collaborative cross strains and their founders

G3: Genes, Genomes, Genetics

Volumn 7, Issue 6, 2017, Pages 1623-1630

  Oreper, Daniel ^a,b   Cai, Yanwei ^a,b   Tarantino, Lisa M ^a,b   de Villena, Fernando Pardo Manuel ^a,b   Valdar, William ^a,b  

^a University of North Carolina   (United States)

^b UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

Collaborative Cross; Haplotype; Inbred strain online GUI; MPP; Multiparental populations; Variant imputation

Indexed keywords

DATA BASE; EXON; GENETIC DIFFERENCE; GENOME; HAPLOTYPE; HUMAN; INBRED STRAIN; METADATA; SCIENTIST; SIMULATION; UNCERTAINTY; ALGORITHM; ANIMAL; BREEDING; COMPUTER INTERFACE; COMPUTER SIMULATION; CROSS BREEDING; GENETIC DATABASE; GENETIC VARIATION; GENOMICS; GENOTYPE; INBRED MOUSE STRAIN; MOUSE; PROCEDURES; WEB BROWSER; WORKFLOW;

ALGORITHMS; ANIMALS; BREEDING; COMPUTER SIMULATION; CROSSES, GENETIC; DATABASES, GENETIC; GENETIC VARIATION; GENOMICS; GENOTYPE; HAPLOTYPES; MICE; MICE, INBRED STRAINS; USER-COMPUTER INTERFACE; WEB BROWSER; WORKFLOW;

EID: 85020250852     PISSN: None     EISSN: 21601836     Source Type: Journal    
DOI: 10.1534/g3.117.041491     Document Type: Article

References (46)

1. Aylor, D. L., W. Valdar, W. Foulds-Mathes, R. J. Buus, R. A. Verdugo et al., 2011 Genetic analysis of complex traits in the emerging collaborative cross. Genome Res. 21: 1213-1222
2. Browning, B. L., and S. R. Browning, 2009 A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am. J. Hum. Genet. 84: 210-223
3. Collaborative Cross Consortium, 2012 The genome architecture of the collaborative cross mouse genetic reference population. Genetics 190: 389-401
4. Danecek, P., A. Auton, G. Abecasis, C. A. Albers, E. Banks et al., 2011 The variant call format and VCFtools. Bioinformatics 27: 2156-2158
5. Ferris, M. T., D. L. Aylor, D. Bottomly, A. C. Whitmore, L. D. Aicher et al., 2013 Modeling host genetic regulation of influenza pathogenesis in the collaborative cross. PLoS Pathog. 9: e1003196
6. Fu, C.-P., C. E. Welsh, F. P.-M. de Villena, and L. McMillan, 2012 Inferring ancestry in admixed populations using microarray probe intensities. Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine, Orlando, FL, pp. 105-112
7. Gatti, D. M., K. L. Svenson, A. Shabalin, L.-Y. Wu, W. Valdar et al., 2014 Quantitative trait locus mapping methods for diversity outbred mice. G3 (Bethesda) 4: 1623-1633
8. Gralinski, L. E., V. D. Menachery, A. P. Morgan, A. Totura, A. Beall et al., 2017 Allelic variation in mouse Ticam2 contributes to SARS-CoV pathogenesis. G3 (Bethesda) 7: 1653-1663
9. Green, R., C. Wilkins, S. Thomas, A. Sekine, D. M. Hendrick et al., 2017 Oas1b-dependent immune transcriptional profiles of West Nile virus infection in the collaborative cross. G3 (Bethesda) 7: 1665-1682
10. Guan, Y., and M. Stephens, 2008 Practical issues in imputation-based association mapping. PLoS Genet. 4: e1000279
11. Hawley, M. E., and K. K. K. Kidd, 1995 HAPLO-a program using the EM algorithm to estimate the frequencies of multisite haplotypes. J. Hered. 86: 409-411
12. Hickey, J. M., B. P. Kinghorn, B. Tier, J. H. J. van der Werf, and M. A. Cleveland, 2012 A phasing and imputation method for pedigreed populations that results in a single-stage genomic evaluation. Genet. Sel. Evol. 44: 9
13. Howie, B. N., P. Donnelly, and J. Marchini, 2009 A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5: e1000529
14. Huang, S., C.-Y. Kao, L. McMillan, and W. Wang, 2013 Transforming genomes using MOD files with applications. Proceedings of the International Conference on Bioinformatics, Computational Biology and Biomedical Informatics, Washington DC, p. 595
15. Keane, T. M., L. Goodstadt, P. Danecek, M. A. White, K. Wong et al., 2011 Mouse genomic variation and its effect on phenotypes and gene regulation. Nature 477: 289-294
16. King, E. G., S. J. Macdonald, and A. D. Long, 2012 Properties and power of the Drosophila synthetic population resource for the routine dissection of complex traits. Genetics 191: 935-949
17. Kutalik, Z., T. Johnson, M. Bochud, V. Mooser, P. Vollenweider et al., 2011 Methods for testing association between uncertain genotypes and quantitative traits. Biostatistics 12: 1-17
18. Li, Y., C. Willer, S. Sanna, and G. Abecasis, 2009 Genotype imputation. Annu. Rev. Genomics Hum. Genet. 10: 387-406
19. Li, Y., C. J. Willer, J. Ding, P. Scheet, and G. R. Abecasis, 2010 MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes. Genet. Epidemiol. 34: 816-834
20. Liu, E. Y., Q. Zhang, L. McMillan, F. Pardo-Manuel de Villena, and W. Wang, 2010 Efficient genome ancestry inference in complex pedigrees with inbreeding. Bioinformatics 26: i199-i207
21. Marchini, J., and B. Howie, 2010 Genotype imputation for genome-wide association studies. Nat. Rev. Genet. 11: 499-511
22. Marchini, J., B. N. Howie, S. Myers, G. McVean, and P. Donnelly, 2007 A new multipoint method for genome-wide association studies by imputation of genotypes. Nat. Genet. 39: 906-913
23. McLaren, W., B. Pritchard, D. Rios, Y. Chen, P. Flicek et al., 2010 Deriving the consequences of genomic variants with the Ensembl API and SNP effect predictor. Bioinformatics 26: 2069-2070
24. Morgan, A. P., and C. E. Welsh, 2015 Informatics resources for the collaborative cross and related mouse populations. Mamm. Genome 26: 521-539
25. Morgan, A. P., C.-P. Fu, C.-Y. Kao, C. E. Welsh, J. P. Didion et al., 2015 The mouse universal genotyping array: from substrains to subspecies. G3 6: 263-279
26. Morgan, A. P., D. M. Gatti, T. M. Keane, R. J. Galante, A. I. Pack et al., 2017 Structural variation shapes the landscape of recombination in mouse. Genetics 206: 603-619
27. Mosedale, M., Y. Kim, W. J. Brock, S. E. Roth, T. Wiltshire et al., 2017 Candidate risk factors and mechanisms for Tolvaptan-induced liver injury are identified using a collaborative cross approach. Toxicol. Sci
28. Mott, R., C. J. Talbot, M. G. Turri, A. C. Collins, and J. Flint, 2000 A method for fine mapping quantitative trait loci in outbred animal stocks. Proc. Natl. Acad. Sci. USA 97: 12649-12654
29. Oreper, D., Y. Cai, L. M. Tarantino, F. Pardo-Manuel de Villena, and W. Valdar, 2017a Github repository. Available at: https://github.com/danoreper/ISVdb.gi
30. Oreper, D., Y. Cai, L. M. Tarantino, F. Pardo-Manuel de Villena, and W. Valdar, 2017b Zenodo repository. Available at: https://doi.org/10.5281/zenodo.399474
31. Phillippi, J., Y. Xie, D. R. Miller, T. A. Bell, Z. Zhang et al., 2014 Using the emerging collaborative cross to probe the immune system. Genes Immun. 15: 38-46
32. R Core Team, 2015 R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria
33. Ramasamy, A., D. Trabzuni, J. R. Gibbs, A. Dillman, D. G. Hernandez et al., 2013 Resolving the polymorphism-in-probe problem is critical for correct interpretation of expression QTL studies. Nucleic Acids Res. 41: e88
34. Rasmussen, A. L., A. Okumura, M. T. Ferris, R. Green, F. Feldmann et al., 2014 Host genetic diversity enables Ebola hemorrhagic fever pathogenesis and resistance. Science 346: 987-991
35. Sargolzaei, M., J. P. Chesnais, and F. S. Schenkel, 2014 A new approach for efficient genotype imputation using information from relatives. BMC Genomics 15: 478
36. Scheet, P., and M. Stephens, 2006 A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase. Am. J. Hum. Genet. 78: 629-644
37. Shorter, J. R., F. Odet, D. L. Aylor, W. Pan, K. Chia-Yu et al., 2017 Male infertility is responsible for nearly half of the extinction observed in the collaborative cross. Genetics 206: 557-572
38. Srivastava, A., A. P. Morgan, M. Najarian, V. K. Sarsani, J. S. Sigmon et al., 2017 The genomes of the collaborative cross. Genetics 206: 537-556
39. Tian, F., P. J. Bradbury, P. J. Brown, H. Hung, Q. Sun et al., 2011 Genomewide association study of leaf architecture in the maize nested association mapping population. Nat. Genet. 43: 159-162
40. VanRaden, P. M., J. R. O'Connell, G. R. Wiggans, and K. A. Weigel, 2011 Genomic evaluations with many more genotypes. Genet. Sel. Evol. 43: 10
41. Verbyla, A. P., A. W. George, C. R. Cavanagh, and K. L. Verbyla, 2014 Wholegenome QTL analysis for MAGIC. Theor. Appl. Genet. 127: 1753-1770
42. Welsh, C. E., D. R. Miller, K. F. Manly, J. Wang, L. McMillan et al., 2012 Status and access to the collaborative cross population. Mamm. Genome 23: 706-712
43. Yalcin, B., J. Flint, and R. Mott, 2005 Using progenitor strain information to identify quantitative trait nucleotides in outbred mice. Genetics 171: 673-681
44. Zhang, Z., W. Wang, and W. Valdar, 2014 Bayesian modeling of haplotype effects in multiparent populations. Genetics 198: 139-156
45. Zheng, C., M. P. Boer, and F. A. van Eeuwijk, 2015 Reconstruction of genome ancestry blocks in multiparental populations. Genetics 200: 1073-1087
46. Zheng, J., Y. Li, G. R. Abecasis, and P. Scheet, 2011 A comparison of approaches to account for uncertainty in analysis of imputed genotypes. Genet. Epidemiol. 35: 102-110