title: COIL: a methodology for evaluating malarial complexity of infection using likelihood from single nucleotide polymorphism data.
abstract: BACKGROUND
  Complex malaria infections are defined as those containing more than one genetically distinct lineage of Plasmodium parasite. Complexity of infection (COI) is a useful parameter to estimate from patient blood samples because it is associated with clinical outcome, epidemiology and disease transmission rate. This manuscript describes a method for estimating COI using likelihood, called COIL, from a panel of bi-allelic genotyping assays.
  
  
  METHODS
  COIL assumes that distinct parasite lineages in complex infections are unrelated and that genotyped loci do not exhibit significant linkage disequilibrium. Using the population minor allele frequency (MAF) of the genotyped loci, COIL uses the binomial distribution to estimate the likelihood of a COI level given the prevalence of observed monomorphic or polymorphic genotypes within each sample.
  
  
  RESULTS
  COIL reliably estimates COI up to a level of three or five with at least 24 or 96 unlinked genotyped loci, respectively, as determined by in silico simulation and empirical validation. Evaluation of COI levels greater than five in patient samples may require a very large collection of genotype data, making sequencing a more cost-effective approach for evaluating COI under conditions when disease transmission is extremely high. Performance of the method is positively correlated with the MAF of the genotyped loci. COI estimates from existing SNP genotype datasets create a more detailed portrait of disease than analyses based simply on the number of polymorphic genotypes observed within samples.
  
  
  CONCLUSIONS
  The capacity to reliably estimate COI from a genome-wide panel of SNP genotypes provides a potentially more accurate alternative to methods relying on PCR amplification of a small number of loci for estimating COI. This approach will also increase the number of applications of SNP genotype data, providing additional motivation to employ SNP barcodes for studies of disease epidemiology or control measure efficacy. The COIL program is available for download from GitHub, and users may also upload their SNP genotype data to a web interface for simple and efficient determination of sample COI.
authors.affiliation: Department of Biostatistics, Harvard School of Public Health, Boston, MA, 02115, USA. kgalinsky@gmail.com.
authors.forename: Kevin
authors.initials: K
authors.lastname: Galinsky
authors.affiliation: Department of Immunology and Infectious Disease, Harvard School of Public Health, Boston, MA, 02115, USA. cvalim@hsph.harvard.edu.
authors.forename: Clarissa
authors.initials: C
authors.lastname: Valim
authors.affiliation: Laboratoire de Parasitologie, National Reference Centre for Malaria, Institut Pasteur de la Guyane, Cayenne, French Guiana, France. Arielle.salmier@gmail.com.
authors.forename: Arielle
authors.initials: A
authors.lastname: Salmier
authors.affiliation: Laboratoire de Parasitologie, National Reference Centre for Malaria, Institut Pasteur de la Guyane, Cayenne, French Guiana, France. bdethoisy@pasteur-cayenne.fr.
authors.forename: Benoit
authors.initials: B
authors.lastname: de Thoisy
authors.affiliation: Laboratoire de Parasitologie, National Reference Centre for Malaria, Institut Pasteur de la Guyane, Cayenne, French Guiana, France. lmusset@pasteur-cayenne.fr.
authors.forename: Lise
authors.initials: L
authors.lastname: Musset
authors.affiliation: Laboratoire de Parasitologie, National Reference Centre for Malaria, Institut Pasteur de la Guyane, Cayenne, French Guiana, France. elegrand@pasteur-cayenne.fr.
authors.forename: Eric
authors.initials: E
authors.lastname: Legrand
authors.affiliation: Faculty of Arts and Sciences, Harvard University, Cambridge, MA, 02138, USA. afaust@college.harvard.edu.
authors.forename: Aubrey
authors.initials: A
authors.lastname: Faust
authors.affiliation: Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. baniecki@broadinstitute.org.
authors.forename: Mary Lynn
authors.initials: ML
authors.lastname: Baniecki
authors.affiliation: Faculty of Medicine and Pharmacy, Cheikh Anta Diop University, Dakar, Senegal. daouda.ndiaye@ucad.edu.sn.
authors.forename: Daouda
authors.initials: D
authors.lastname: Ndiaye
authors.affiliation: Faculty of Arts and Sciences, Harvard University, Cambridge, MA, 02138, USA. rdaniels@broadinstitute.org.|Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. rdaniels@broadinstitute.org.
authors.forename: Rachel F
authors.initials: RF
authors.lastname: Daniels
authors.affiliation: Faculty of Arts and Sciences, Harvard University, Cambridge, MA, 02138, USA. dhartl@oeb.harvard.edu.|Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. dhartl@oeb.harvard.edu.
authors.forename: Daniel L
authors.initials: DL
authors.lastname: Hartl
authors.affiliation: Faculty of Arts and Sciences, Harvard University, Cambridge, MA, 02138, USA. pardis@broadinstitute.org.|Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. pardis@broadinstitute.org.
authors.forename: Pardis C
authors.initials: PC
authors.lastname: Sabeti
authors.affiliation: Department of Immunology and Infectious Disease, Harvard School of Public Health, Boston, MA, 02115, USA. dfwirth@hsph.harvard.edu.|Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. dfwirth@hsph.harvard.edu.
authors.forename: Dyann F
authors.initials: DF
authors.lastname: Wirth
authors.affiliation: Department of Immunology and Infectious Disease, Harvard School of Public Health, Boston, MA, 02115, USA. svolkman@hsph.harvard.edu.|Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. svolkman@hsph.harvard.edu.|Simmons College School of Nursing and Health Sciences, Boston, MA, 02115, USA. svolkman@hsph.harvard.edu.
authors.forename: Sarah K
authors.initials: SK
authors.lastname: Volkman
authors.affiliation: Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA. neafsey@broadinstitute.org.
authors.forename: Daniel E
authors.initials: DE
authors.lastname: Neafsey
mesh_terms: D019295:Computational Biology / Q000379:methods*; D016054:DNA, Protozoan / Q000235:genetics; D005787:Gene Frequency / Q000235:genetics; D005838:Genotype; D006801:Humans; D008288:Malaria / Q000145:classification / Q000469:parasitology* / Q000503:physiopathology; D015233:Models, Statistical; D010961:Plasmodium / Q000235:genetics*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012984:Software
chemical_list: D016054:DNA, Protozoan