We used DNA from over 4,000 children ascertained with severe malaria in the period 1995-2009 to test for association between human and P.falciparum genetic variants. All individuals were from Banjul, The Gambia, and from Kilifi County, Kenya, and were previously analysed for human genotypes (see doi:10.1038/s41467-019-13480-z and https://www.malariagen.net/resource/25). For this study, we generated P.falciparum genome sequence reads using the Illumina X Ten platform and used this to identify and call parasite genetic variation. We then tested for association between human and parasite variants using a logistic regression approach implemented in the software HPTEST (https://www.well.ox.ac.uk/~gav/hptest). More information about the methodology is available on the data resource page: https://www.malariagen.net/resource/32. Full details of our data generation and processing are available in the manuscript: Band, G., Leffler, E.M., Jallow, M. et al. Malaria protection due to sickle haemoglobin depends on parasite genotype. Nature (2021). https://doi.org/10.1038/s41586-021-04288-3.
Available software
Two two software packages were developed to to conduct the analysis in the associated paper and has been made freely available:
- Software for human-parasite association testing. The HPTEST software can be used to test for association between host and pathogen genotypes using a logistic regression approach. Full documentation can be found at https://www.well.ox.ac.uk/~gav/hptest.
- Software for computing linkage disequilibrium (LD) metrics. The LDBIRD software can be used to compute between-locus LD metrics in human or parasite data. Full documentation can be found at https://www.well.ox.ac.uk/~gav/ldbird.
Source code for both packages is available as part of the QCTOOL package (https://code.enkre.net/qctool) under an open-source license. A snapshot of this code has also been deposited on Zenodo (https://doi.org/10.5281/zenodo.5685580).