Replication Data for: Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data

Version 4.0
Ndila, Carolyne M.; Nyirongo, Vysaul; Macharia, Alexander W.; Jeffreys, Anna E.; Rowlands, Kate; Hubbart, Christina; Busby, George B. J.; Band, Gavin; Harding, Rosalind; Rockett, Kirk A.; Williams, Thomas N.; the MalariaGEN Consortium, 2020, "Replication Data for: Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the ‑α3.7I form of α-thalassaemia using genome-wide microarray data", https://doi.org/10.7910/DVN/YTXAHR, Harvard Dataverse, V4, UNF:6:6YD+L93LLD7FbMgF6sUNIQ== [fileUNF]
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Description

This is a replication dataset for the submitted manuscript: "Haplotype heterogeneity and low linkage disequilibrium reduce reliable prediction of genotypes for the α3.7I form of α-thalassaemia using genome-wide microarray data".

The dataset contains genotyped α-thalassemia mutations from more than 6,000 individuals from Kilifi, Kenya. These data along with their corresponding Illumina HumanOmni2.5-4 microarray data was used to investigate the haplotype structure of α-thalassemia deletion variants in the population, and the potential utility of a wide range of indirect GWAS-based approaches, including the microarray-chip intensity data and haplotype imputation, as an alternative to direct typing.

Version notes: This revision was made following review of the primary manuscript related to this data package and includes 2 updated files and an additional data file with associated descriptions file.

Subject Medicine, Health and Life Sciences
Keyword Malaria, α-thalassemia, Predictive Models, multinomial regression-model, Classification and Regression Tree, GWAS, haplotypes
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License: Creative Commons Attribution 4.0 International

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