Af1.4
Contents
Af1.4#
The Af1.4: Anopheles gambiae data resource contains single nucleotide polymorphism (SNP) calls and SNP haplotypes from whole-genome sequencing of 733 mosquitoes.
More information about this release can be found in the data resource website.
This page provides an introduction to open data resources released as part of Af1.4
.
If you have any questions about this guide or how to use the data, please start a new discussion on the malariagen/vector-open-data repo on GitHub. If you find any bugs, please raise an issue.
Terms of use#
Data from this project will be made publicly available before journal publication. Unless otherwise stated, analyses of project data are ongoing and publications are in preparation by project partners, and it is not permitted to use project data for publication (including any type of communication with the general public) without prior permission from the originating partner studies.
Although malaria is generally an endemic rather than an epidemic disease, and the focus of this project is on surveillance of disease vectors rather than pathogens, our data terms of use build on MalariaGEN’s approach to data sharing, and adopt norms which have been established for rapid sharing of pathogen genomic data during disease outbreaks. The primary rationale for this approach is that malaria remains a public health emergency, where ethically appropriate and rapid sharing of genomic surveillance data can help to detect and respond to biological threats such as new forms of insecticide resistance, and to adapt malaria vector control strategies to different settings and changing circumstances.
The publication embargo for all data on this release will expire on the 16th of August 2026.
If you have any questions about the terms of use, please email support@malariagen.net
Partner studies#
1188-VO-SN-NIANG - Anopheles gambiae vector surveillance in Senegal.
1330-VO-GN-LAMA - Anopheles gambiae vector surveillance in Guinea.
1354-VO-KE-DONNELLY - Anopheles vector surveillance in Kenya.
Whole-genome sequencing and variant calling#
All samples in Af1.4
have been sequenced individually to high coverage using Illumina technology at the Wellcome Sanger Institute. These sequence data have then been analysed to identify genetic variants such as single nucleotide polymorphisms (SNPs). After variant calling, both the samples and the variants have been through a range of quality control analyses, to ensure the data are of high quality. Both the raw sequence data and the curated variant calls are openly available for download and analysis.
Data hosting#
Data from Af1.4
are hosted by several different services.
The SNP data have also been uploaded to Google Cloud, and can be analysed directly within the cloud without having to download or copy any data, including via free interactive computing services such as MyBinder and Google Colab. Further information about analysing these data in the cloud is provided in the cloud data access guide.
Sample sets#
The samples included in Af1.4
have been organised into 1 sample set.
Each sample set corresponds to a set of mosquito specimens from a contributing study. Study details can be found in the partner studies webpages listed above.
Note: To access the Af1.4
release, you need to use the pre=True
flag.
This flag is used when more data will be added to this release, for the case of Af1.4
, CNV data for the sample sets on this release will be included at a future date.
sample_set | sample_count | |
---|---|---|
study_id | ||
1188-VO-SN-NIANG | 1188-VO-NIANG-NIEL-SN-2304-VMF00259 | 71 |
1330-VO-GN-LAMA | 1330-VO-GN-LAMA-VMF00250 | 196 |
1354-VO-KE-DONNELLY | 1354-VO-KE-DONNELLY-VMF00281 | 466 |
Here is a more detailed breakdown of the samples contained within this sample set, summarised by country, year of collection, and species:
taxon | funestus | |||
---|---|---|---|---|
study_id | sample_set | country | year | |
1188-VO-SN-NIANG | 1188-VO-NIANG-NIEL-SN-2304-VMF00259 | Senegal | 2020 | 11 |
2021 | 16 | |||
2022 | 44 | |||
1330-VO-GN-LAMA | 1330-VO-GN-LAMA-VMF00250 | Guinea | 2022 | 196 |
1354-VO-KE-DONNELLY | 1354-VO-KE-DONNELLY-VMF00281 | Kenya | 2023 | 466 |
Note that there can be multiple sampling sites represented within the same sample set.
Further reading#
We hope this page has provided a useful introduction to the Af1.4
data resource. If you would like to start working with these data, please visit the cloud data access guide or the data download guide or continue browsing the other documentation on this site.
If you have any questions about the data and how to use them, please do get in touch by starting a new discussion on the malariagen/vector-data repository on GitHub.