Abstract
In this chapter, we will review current statistical and computational approaches for genotype calling and haplotype phasing from next generation data. We will focus on statistical ideas and ignore many practical bioinformatics issues such as image processing for base calling, read mapping, sequencing error rate recalibration, etc, each of which is a topic in its own right. We will give derivations of commonly used approaches, emphasize their assumptions, and aim to unify them in an all-encompassing Bayesian framework. We will point out limitations of single-site genotype likelihood methods that dominate current practice and discuss strategies to use haplotype informative reads.
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Acknowledgements
This work is partly supported by National Institute of Health (NIH) grant R00 RR024163. Computational portions of this research were supported by NIH S10RR026723.
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Zhi, D., Zhang, K. (2014). Genotype Calling and Haplotype Phasing from Next Generation Sequencing Data. In: Datta, S., Nettleton, D. (eds) Statistical Analysis of Next Generation Sequencing Data. Frontiers in Probability and the Statistical Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-07212-8_16
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DOI: https://doi.org/10.1007/978-3-319-07212-8_16
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