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    An open dataset of genome variation in 7,000 worldwide samples

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    Author
    Ahouidi, Ambroise
    Ali, Mozam
    Almagro-Garcia, Jacob
    Amambua-Ngwa, Alfred
    Amaratunga, Chanaki
    Amato, Roberto
    Amenga-Etego, Lucas
    Andagalu, Ben
    Anderson, Tim J C
    Andrianaranjaka, Voahangy
    Apinjoh, Tobias
    Ariani, Cristina
    Ashley, Elizabeth A
    Auburn, Sarah
    Awandare, Gordon
    Ba, Hampate
    Baraka, Vito
    Barry, Alyssa E
    Bejon, Philip
    Bertin, Gwladys I
    Boni, Maciej F
    Borrmann, Steffen
    Bousema, Teun
    Branch, Oralee
    Bull, Peter C
    Busby, George B J
    Chookajorn, Thanat
    Chotivanich, Kesinee
    Claessens, Antoine
    Conway, David
    Craig, Alister
    D'Alessandro, Umberto
    Dama, Souleymane
    Day, Nicholas Pj
    Denis, Brigitte
    Diakite, Mahamadou
    Djimdé, Abdoulaye
    Dolecek, Christiane
    Dondorp, Arjen M
    Drakeley, Chris
    Drury, Eleanor
    Duffy, Patrick
    Echeverry, Diego F
    Egwang, Thomas G
    Erko, Berhanu
    Fairhurst, Rick M
    Faiz, Abdul
    Fanello, Caterina A
    Fukuda, Mark M
    Gamboa, Dionicia
    Ghansah, Anita
    Golassa, Lemu
    Goncalves, Sonia
    Hamilton, William L
    Harrison, G L Abby
    Hart, Lee
    Henrichs, Christa
    Hien, Tran Tinh
    Hill, Catherine A
    Hodgson, Abraham
    Hubbart, Christina
    Imwong, Mallika
    Ishengoma, Deus S
    Jackson, Scott A
    Jacob, Chris G
    Jeffery, Ben
    Jeffreys, Anna E
    Johnson, Kimberly J
    Jyothi, Dushyanth
    Kamaliddin, Claire
    Kamau, Edwin
    Kekre, Mihir
    Kluczynski, Krzysztof
    Kochakarn, Theerarat
    Konaté, Abibatou
    Kwiatkowski, Dominic P
    Kyaw, Myat Phone
    Lim, Pharath
    Lon, Chanthap
    Loua, Kovana M
    Maïga-Ascofaré, Oumou
    Malangone, Cinzia
    Manske, Magnus
    Marfurt, Jutta
    Marsh, Kevin
    Mayxay, Mayfong
    Miles, Alistair
    Miotto, Olivo
    Mobegi, Victor
    Mokuolu, Olugbenga A
    Montgomery, Jacqui
    Mueller, Ivo
    Newton, Paul N
    Nguyen, Thuy
    Nguyen, Thuy-Nhien
    Noedl, Harald
    Nosten, Francois
    Noviyanti, Rintis
    Nzila, Alexis
    Ochola-Oyier, Lynette I
    Ocholla, Harold
    Oduro, Abraham
    Omedo, Irene
    Onyamboko, Marie A
    Ouedraogo, Jean-Bosco
    Oyebola, Kolapo
    Pearson, Richard D
    Peshu, Norbert
    Phyo, Aung Pyae
    Plowe, Chris V
    Price, Ric N
    Pukrittayakamee, Sasithon
    Randrianarivelojosia, Milijaona
    Rayner, Julian C
    Ringwald, Pascal
    Rockett, Kirk A
    Rowlands, Katherine
    Ruiz, Lastenia
    Saunders, David
    Shayo, Alex
    Siba, Peter
    Simpson, Victoria J
    Stalker, Jim
    Su, Xin-Zhuan
    Sutherland, Colin
    Takala-Harrison, Shannon
    Tavul, Livingstone
    Thathy, Vandana
    Tshefu, Antoinette
    Verra, Federica
    Vinetz, Joseph
    Wellems, Thomas E
    Wendler, Jason
    White, Nicholas J
    Wright, Ian
    Yavo, William
    Ye, Htut
    Show allShow less

    Date
    2021-02-24
    Journal
    Wellcome Open Research
    Publisher
    Wellcome Trust
    Type
    Article
    
    Metadata
    Show full item record
    See at
    https://doi.org/10.12688/wellcomeopenres.16168.1
    Abstract
    MalariaGEN is a data-sharing network that enables groups around the world to work together on the genomic epidemiology of malaria. Here we describe a new release of curated genome variation data on 7,000 Plasmodium falciparum samples from MalariaGEN partner studies in 28 malaria-endemic countries. High-quality genotype calls on 3 million single nucleotide polymorphisms (SNPs) and short indels were produced using a standardised analysis pipeline. Copy number variants associated with drug resistance and structural variants that cause failure of rapid diagnostic tests were also analysed.  Almost all samples showed genetic evidence of resistance to at least one antimalarial drug, and some samples from Southeast Asia carried markers of resistance to six commonly-used drugs. Genes expressed during the mosquito stage of the parasite life-cycle are prominent among loci that show strong geographic differentiation. By continuing to enlarge this open data resource we aim to facilitate research into the evolutionary processes affecting malaria control and to accelerate development of the surveillance toolkit required for malaria elimination.
    Rights/Terms
    Copyright: © 2021 MalariaGEN et al.
    Keyword
    data resource
    drug resistance
    evolution
    genomic epidemiology
    genomics
    malaria
    plasmodium falciparum
    population genetics
    rapid diagnostic test failure
    Identifier to cite or link to this item
    http://hdl.handle.net/10713/15134
    ae974a485f413a2113503eed53cd6c53
    10.12688/wellcomeopenres.16168.1
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