Software to test for genetic association between hosts and pathogens.


HPTEST is a command-line program to test for association between genotypes at pairs of genetic variants. The motivating use case is to test for association between hosts and pathogens, using genotype data from hosts and from the pathogens infecting those hosts, but HPTEST also has other potential use-cases, such as estimating LD between variants while controlling for confounding variables.

The method currently implemented in HPTEST is logistic regression in which one set of genotypes (e.g. the host genotypes) are included as predictors and the second set (e.g. pathogen genotypes) are included as the outcome. Covariates can also be included. For each pair of variants, HPTEST outputs the genotype counts and a summary of the evidence for association.

For an introduction to running HPTEST, please see the getting started page.

Obtaining and running HPTEST

HPTEST is currently included as part of the QCTOOL package, which is currently hosted at code.enkre.net. See the download page for full details on obtaining and installing HPTEST.


HPTEST was originally developed for a study of human and malaria parasite variation in samples collected for MalariaGEN Consortial Project 1. If you use HPTEST in published work, please cite the following preprint (or its published equivalent):

"The protective effect of sickle cell haemoglobin against severe malaria depends on parasite genotype", bioRxiv https://doi.org/10.1101/2021.03.30.437659
Gavin Band, Ellen M. Leffler, Muminatou Jallow, Fatoumatta Sisay-Joof, Carolyne M. Ndila, Alexander W. Macharia, Christina Hubbart, Anna E. Jeffreys, Kate Rowlands, Thuy Nguyen, Sonia M. Goncalves, Cristina V. Ariani, Jim Stalker, Richard D. Pearson, Roberto Amato, Eleanor Drury, Giorgio Sirugo, Umberto d'Alessandro, Kalifa A. Bojang, Kevin Marsh, Norbert N.P. Peshu, David J. Conway, Thomas N. Williams, Kirk A. Rockett, Dominic P. Kwiatkowski


For more information or questions, please contact me at gavin [dot] band (at) well.ox.ac.uk.