Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

pahanc/mapping-vgsc-allele-frequencies: mapping-vgsc-allele-frequencies

Domaine:

healthcaregeospatial

Type de record:

software
Créateur:
Penny Hancock
Éditeur:
Zenodo
Hôte:avatar

This directory contains code for running stacked generalisation geospatial modelling analyses described in :

"Hancock, P.A., Lynd, A., Wiebe, A., Devine, M., Essandoh, J., Wat'senga, F., Manzambi, E., Agossa, F., Donnelly, M.J., Weetman, D., Moyes, C.L., 2022, Modelling spatiotemporal trends in the frequency of genetic mutations conferring insecticide target-site resistance in African malaria vector species", BMC Biology"

The method performs spatiotemporal prediction of the frequencies of three Vgsc alleles in mosquito samples: Vgsc-995L, Vgsc-995F and Vgsc-995S. Mosquito samples contain the following species from the Anopheles gambiae complex: An. gambiae, An. coluzzii, An. arabiensis.

Individual directories contain the code for running the level-0 machine-learning models, including the extreme gradient boosting (xgb), random forest (rf) and neural network (nn) models, and the multinomial meta-model.

System requirements: Code for runnning the xgb and inla models is written in R software, which runs on a wide variety of UNIX platforms, Windows and Mac OS. The R software is open source and quick to install. Code for running the rf and mlp models is written in open source Python software, installed using the Anaconda platform.

Software requirements: R, using the following packages: R-INLA LaplacesDemon zoo mboost xgboost data.table caret

The R code has been tested on R version 3.5.0 with the package R-INLA version 17.06.2, the package xgboost version 0.71.2, and the package data.table version 1.12.8.

The Python code has been tested on python version 3.6.8 with the package keras version 2.2.4 and the package sklearn version 0.20.3.

Visit

doi.org

Languages

NsengaTumbuka

Licenses

info:eu-repo/semantics/openAccessOther (Open)

Similaires

Vgsc allele frequencies in African malaria vector species: field data and predictive map data gridsEvolution of the Pyrethroids Target-Site Resistance Mechanisms in Senegal: Early Stage of the Vgsc-1014F and Vgsc-1014S Allelic Frequencies ShiftCharacteristics and allele frequencies of the chemokine receptor variants.Tunisian population allele frequencies for 15 PCR-based lociKIR allele frequencies in a Xhosa population from South AfricaAllele frequencies and tests of association for the most significant SNPs.

Vgsc allele frequencies in African malaria vector species: field data and predictive map data grids

Predictions for the frequency of alleles of the voltage gated sodium channel gene (Vgsc) were produc

Evolution of the Pyrethroids Target-Site Resistance Mechanisms in Senegal: Early Stage of the Vgsc-1014F and Vgsc-1014S Allelic Frequencies Shift

The evolution and spread of insecticide resistance mechanisms amongst malaria vectors across the sub

Characteristics and allele frequencies of the chemokine receptor variants.

1

Chromosome position is based on the NCBI genome build 36.3;

2

TM, Transmembrane domain; ECL

Tunisian population allele frequencies for 15 PCR-based loci

KIR allele frequencies in a Xhosa population from South Africa

Allele frequencies and tests of association for the most significant SNPs.

Any_malaria group consisted of: clinical malaria, asymptomatic infection and previous hist