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CluStrat: A Structure Informed Clustering Strategy for Population Stratification

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Research in Computational Molecular Biology (RECOMB 2020)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 12074))

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Abstract

Genome-wide association studies (GWAS) have been extensively used to estimate the signed effects of trait-associated alleles. One of the key challenges in GWAS are confounding factors, such as population stratification, which can lead to spurious genotype-trait associations. Recent independent studiesĀ [1, 8, 10] failed to replicate the strong evidence of previously reported signals of directional selection on height in Europeans in the UK Biobank cohort, and attributed the loss of signal to cryptic relatedness in populations.

Supported by NSF IIS 1715202 and NFS DMS 1760353 awarded to PD and PP.

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Correspondence to Peristera Paschou .

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Bose, A., Burch, M.C., Chowdhury, A., Paschou, P., Drineas, P. (2020). CluStrat: A Structure Informed Clustering Strategy for Population Stratification. In: Schwartz, R. (eds) Research in Computational Molecular Biology. RECOMB 2020. Lecture Notes in Computer Science(), vol 12074. Springer, Cham. https://doi.org/10.1007/978-3-030-45257-5_19

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  • DOI: https://doi.org/10.1007/978-3-030-45257-5_19

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-45256-8

  • Online ISBN: 978-3-030-45257-5

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