This resource page accompanies the paper “The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype” which is currently available as a preprint on bioRxiv. This page is under construction and will be expanded to provide information about datasets of human and Plasmodium falciparum genetic variants, genotype calls and sequence reads as these become available. Analysis software generated for the above analysis is also detailed here.
This section is under construction and will be updated with relevant accessions as datasets become available.
For information, this release will contain details on contributing partner studies, samples included in the project, metadata, genomic data, genome-wide genotyping, and several software packages developed for handling such data.
Software for human-parasite association testing:
The HPTEST software used in the above article is available at https://code.enkre.net/qctool. HPTEST is released under the open source Boost Software License. HPTEST version 2.1.9 (revision 7b2ccee228) was used in the above analysis.
Software for computing linkage disequilibrium metrics:
The LDBIRD software used in the paper is available at https://code.enkre.net/qctool. LDBIRD is released under the open source Boost Software License. LDBIRD version 2.1.9 (revision 7b2ccee228) was used in the above analysis.
Please cite the the paper "The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype" if you make use of this software in published work.
Acknowledgements and partner study information
We thank the patients and staff of Kilifi County Hospital and the KEMRI-Wellcome Trust Research Programme, Kilifi for their help with this study, and members of the Human Genetics Group in Kilifi for help with sample collection and processing. We thank the patients and staff at the Paediatric Department of the Royal Victoria Hospital in Banjul, Gambia for their help with the study. The human genetic data used in this study has previously been reported by the Malaria Genomic Epidemiology Network, and we thank all our colleagues who contributed to this previous work as part of MalariaGEN Consortial Project 1.
Publications that have used this data
Human genotyping data used in the paper has previously been published in the following articles and the data is available under managed access terms as described in www.malariagen.net/resource/25.
Malaria Genomic Epidemiology Network, “Insights into malaria susceptibility using genome-wide data on 17,000 individuals from Africa, Asia and Oceania”, Nature Communications (2019) Doi.org/10.1038/s41467-019-13480-z.
Malaria Genomic Epidemiology Network, “Reappraisal of known malaria resistance loci in a large multicenter study”, Nature Genetics (2014) Doi.org/10.1038/ng.3107.