Deconvolution of multiple infections in Plasmodium falciparum from high throughput sequencing data

@article{Zhu2017DeconvolutionOM,
  title={Deconvolution of multiple infections in Plasmodium falciparum from high throughput sequencing data},
  author={Sha Joe Zhu and Jacob Almagro-Garcia and Gil McVean},
  journal={Bioinformatics},
  year={2017},
  volume={34},
  pages={9 - 15}
}
Motivation The presence of multiple infecting strains of the malarial parasite Plasmodium falciparum affects key phenotypic traits, including drug resistance and risk of severe disease. Advances in protocols and sequencing technology have made it possible to obtain high-coverage genome-wide sequencing data from blood samples and blood spots taken in the field. However, analysing and interpreting such data is challenging because of the high rate of multiple infections present. Results We have… 

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An open dataset of Plasmodium falciparum genome variation in 7,000 worldwide samples.

TLDR
A new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries aims to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.

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