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Malaria Vector Genome Observatory

Data for Anopheles mosquito research, surveillance and control.

Data Training API Compute Partners Research

We still have much to learn about the mosquitoes that transmit malaria.

How is malaria being transmitted?

We need a better understanding of which Anopheles mosquito species are transmitting malaria in different places, and how this is changing in response to interventions, urbanisation and climate change.

Where is insecticide resistance evolving and spreading?

Insecticide resistance is the biggest threat to our current tools for mosquito control. When resistance emerges, we need to identify and characterise it quickly, assess the risk, and track it as it spreads.

How can we move beyond control towards elimination?

Our current tools for mosquito control will only take us so far. We need to invent new ways to stop mosquitoes transmitting malaria, and be smart in how we use them.

The observatory is a collaborative effort to sequence the genomes of thousands of Anopheles mosquitoes and use those data to improve malaria control.

The observatory at a glance


Access carefully-curated genomic data which has been optimised for analysis in the cloud.


Learn how to analyse data in the observatory through our hands-on online training course.


Use our open source Python package to explore, visualise and analyse data interactively.


Access free cloud computing services to analyse data wherever you are.


Scientists and engineers from around the globe are contributing samples, data and expertise to help build the observatory.


Data from the observatory are powering new research into vector biology and control.


Access data from whole-genome sequencing of Anopheles mosquitoes collected from natural populations in countries affected by malaria.

Anopheles gambiae complex

19,771 genomes from 31 countries

Anopheles funestus subgroup

3,231 genomes from 16 countries

Anopheles minimus

302 genomes from 1 country


Learn about the biology, technology, data and analytical methods involved in genomic surveillance of Anopheles mosquitoes.

Zoom screen with participants of the PAMCA-MalariaGEN training course

Video lectures in French or English and notebooks with executable code examples.

Study at your own pace, or enroll in an online course to learn alongside others with support from experienced teaching assistants.

Visit training course website


Our cloud-native software for Python supports a range of functions for data access, visualisation and statistical analysis.

Explore available samples by country of origin, collection date and taxon.

Explore available samples by collection location.

Compute frequencies of genetic variants in genes of interest.

Compare the frequency of genetic variants between different geographical areas.

Analyse changes in variant frequencies over time.

Browse sequence read alignments and assess the evidence for genetic variation in individual samples.

Visualise sequence read coverage and evidence for copy number variation in individual samples.

Visualize and compare copy number variation in multiple samples.

Explore population structure with principal components analysis.

Investigate hybridisation and introgression between species with ancestry-informative markers.

Quantify and compare genetic diversity between populations.

Infer runs of homozygosity and investigate evidence for inbreeding.

Perform genome-wide selection scans to discover new resistance genes.

Find genes where adaptive gene flow is occurring between countries or species.

Use haplotype clustering to investigate selective sweeps and gene flow within a gene of interest.

Use haplotype networks to explore selective sweeps and gene flow within a gene of interest.


Run your analysis in the cloud using these computing services.

Google Colab

Colab is an interactive computing service provided for free by Google Research and is ideal for exploratory analyses.

MalariaGEN Datalab

The Genomic Surveillance Unit at the Sanger Institute hosts a JupyterHub service running in Google Cloud that is available for free to observatory partners for more intensive analyses.


Terra is a cloud platform for biomedical research supporting workflows and interactive notebooks, and can be used for a wide range of analyses.

Alternatively, observatory data can be downloaded to your own compute resources to run analyses locally.


Groups and individuals from around the world have contributed biological samples, sequencing capacity, computational resources, time and expertise to build the observatory.

The Pan-African Mosquito Control Association (PAMCA) Anopheles Genomics programme is working to build capacity for malaria vector genomics across Africa.
The Genomics for African Anopheles Resistance (GAARD) project aims to identify new genes and regulatory regions associated with insecticide resistance.
Target Malaria is developing innovative approaches to reduce the population of malaria-transmitting mosquitoes in sub-Saharan Africa.
The PAMGEN project is researching genetic interactions between malaria parasites, vectors and human communities across different African environments.


Data from the observatory are powering new and ongoing research into the biology and control of malaria vectors.

March 01, 2024
Evaluating evidence for co-geography in the Anopheles–Plasmodium host-parasite system
January 27, 2024
Despite structural identity, ace-1 heterogenous duplication resistance alleles are quite diverse in Anopheles mosquitoes
August 16, 2023
Genome-wide association studies reveal novel loci associated with pyrethroid and organophosphate resistance in Anopheles gambiae and Anopheles coluzzii
April 13, 2023
Dispersal inference from population genetic variation using a convolutional neural network
February 06, 2023
Single nucleotide polymorphism (SNP) in the doublesex (dsx) gene splice sites and relevance for its alternative splicing in the malaria vector Anopheles gambiae
January 25, 2023
RNA-Seq-Pop: Exploiting the sequence in RNA-Seq-a Snakemake workflow reveals patterns of insecticide resistance in the malaria vector Anopheles gambiae