Abstract
Computationally inferring the identities and their relative frequencies from pooled samples that are whole-genome or segmentally genotyped or sequenced (e.g., using next-generation sequencing) in a pool is useful for population genetics analysis. To carry out such analysis, one needs to understand basics of how to use high-performance computing (HPC) facilities and the specifics of corresponding computational tools. Here, we describe the basic knowledge and step-by-step usage of a number of tools for haplotype inference on genotyping or next-generation sequencing data.
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Acknowledgment
We are grateful to the communications with Dr. Yaning Yang on PoooL and the communications with Dr. Darren Kessner on HARP. This work was partially supported by the start-up grant of University of Calgary and NIH grants (HG008451 and AG046170)
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Long, Q. (2017). Computational Haplotype Inference from Pooled Samples. In: Tiemann-Boege, I., Betancourt, A. (eds) Haplotyping. Methods in Molecular Biology, vol 1551. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6750-6_15
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DOI: https://doi.org/10.1007/978-1-4939-6750-6_15
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Publisher Name: Humana Press, New York, NY
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Online ISBN: 978-1-4939-6750-6
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