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A Monte Carlo approach to calculating probabilities for continuous identity by descent data

  • Sharon Browning (a1)

Abstract

Two related individuals are identical by descent at a genetic locus if they share the same gene copy at that locus due to inheritance from a recent common ancestor. We consider idealized continuous identity by descent (IBD) data in which IBD status is known continuously along chromosomes. IBD data contains information about the relationship between the two individuals, and about the underlying crossover processes. We present a Monte Carlo method for calculating probabilities for IBD data. The method is not restricted to Haldane's Poisson process model of crossing-over but may be used with other models including the chi-square, Kosambi renewal and Sturt models. Results of a simulation study demonstrate that IBD data can be used to distinguish between alternative models for the crossover process.

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Corresponding author

Postal address: Department of Statistics, North Carolina State University, Raleigh, NC 27695-8203, USA. Email address: browning@stat.nscu.edu

References

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[1] Barnard, G. A. (1963). Discussion of paper by M. S. Bartlett. J. R. Statist. Soc. Ser. B 25, 294.
[2] Boehnke, M., and Cox, N. J. (1997). Accurate inference of relationships in sib-pair linkage studies. Amer. J. Human Genet. 61, 423429.
[3] Broman, K. W., Murray, J. C., Sheffield, V. C., White, R. L., and Weber, J. L. (1998). Comprehensive human genetic maps: individual and sex-specific variation in recombination. Amer. J. Human Genet. 63, 861869.
[4] Browning, S. (1998). Relationship information contained in gamete identity by descent data. J. Comput. Biol. 5, 323334.
[5] Browning, S. (1999). Monte Carlo likelihood calculation for identity by descent data. PhD thesis, University of Washington.% Available at http://statgen.ncsu.edu/sharon/thesis.pdf (822 kb).
[6] Browning, S. (2000). The relationship between count-location and stationary renewal models for the chiasma process. Genetics 155, 19551960.
[7] Efron, B., and Tibshirani, R. (1986). Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy. Statist. Sci. 1, 5475.
[8] Geyer, C. J., Ryder, O. A., Chemnick, L. G., and Thompson, E. A. (1993). Analysis of relatedness in the California condors, from DNA fingerprints. Molec. Biol. Evolut. 10, 571589.
[9] Haldane, J. B. S. (1919). The combination of linkage values, and the calculation of distances between the loci of linked factors. J. Genetics 8, 299309.
[10] Hope, A. C. A. (1968). A simplified Monte Carlo significance test procedure. J. R. Statist. Soc. Ser. B, 30, 582598.
[11] Jöckel, K.-H. (1986). Finite sample properties and asymptotic efficiency of Monte Carlo tests. Ann. Statist. 14, 336347.
[12] Kosambi, D. D. (1944). The estimation of map distances from recombination values. Ann. Eugenics 12, 172175.
[13] Lange, K. (1997). Mathematical and Statistical Methods for Genetic Analysis. Springer, New York, pp. 206227.
[14] Sturt, E. (1976). A mapping function for human chromosomes. Ann. Human Genet. 40, 147163.
[15] Zhao, H., and Liang, F. (2000). On relationship inference using gamete identity by descent data. Unpublished manuscript.
[16] Zhao, H., and Speed, T. P. (1996). On genetic map functions. Genetics 142, 13691377.
[17] Zhao, H., McPeek, M. S., and Speed, T. P. (1995). Statistical analysis of chromatid interference. Genetics 139, 10571065.
[18] Zhao, H., Speed, T. P., and McPeek, M. S. (1995). Statistical analysis of crossover interference using the chi-square model. Genetics 139, 10451056.

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