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1.
Preprint em Inglês | bioRxiv | ID: ppbiorxiv-474610

RESUMO

Massive sequencing of SARS-CoV-2 genomes has led to a great demand for adding new samples to a reference phylogeny instead of building the tree from scratch. To address such challenge, we proposed an algorithm TIPars by integrating parsimony analysis with pre-computed ancestral sequences. Compared to four state-of-the-art methods on four benchmark datasets (SARS-CoV-2, Influenza virus, Newcastle disease virus and 16S rRNA genes), TIPars achieved the best performance in most tests. It took only 21 seconds to insert 100 SARS-CoV-2 genomes to a 100k-taxa reference tree using near 1.4 gigabytes of memory. Its efficient and accurate phylogenetic placements and incrementation for phylogenies with highly similar and divergent sequences suggest that it will be useful in a wide range of studies including pathogen molecular epidemiology, microbiome diversity and systematics.

2.
Raquel Viana; Sikhulile Moyo; Daniel Gyamfi Amoako; Houriiyah Tegally; Cathrine Scheepers; Richard J Lessells; Jennifer Giandhari; Nicole Wolter; Josie Everatt; Andrew Rambaut; Christian Althaus; Eduan Wilkinson; Adriano Mendes; Amy Strydom; Michaela Davids; Simnikiwe Mayaphi; Simani Gaseitsiwe; Wonderful T Choga; Dorcas Maruapula; Boitumelo Zuze; Botshelo Radibe; Legodile Koopile; Roger Shapiro; Shahin Lockman; Mpaphi B. Mbulawa; Thongbotho Mphoyakgosi; Pamela Smith-Lawrence; Mosepele Mosepele; Mogomotsi Matshaba; Kereng Masupu; Mohammed Chand; Charity Joseph; Lesego Kuate-Lere; Onalethatha Lesetedi-Mafoko; Kgomotso Moruisi; Lesley Scott; Wendy Stevens; Constantinos Kurt Wibmer; Anele Mnguni; Arshad Ismail; Boitshoko Mahlangu; Darren P. Martin; Verity Hill; Rachel Colquhoun; Modisa S. Motswaledi; James Emmanuel San; Noxolo Ntuli; Gerald Motsatsi; Sureshnee Pillay; Thabo Mohale; Upasana Ramphal; Yeshnee Naidoo; Naume Tebeila; Marta Giovanetti; Koleka Mlisana; Carolyn Williamson; Nei-yuan Hsiao; Nokukhanya Msomi; Kamela Mahlakwane; Susan Engelbrecht; Tongai Maponga; Wolfgang Preiser; Zinhle Makatini; Oluwakemi Laguda-Akingba; Lavanya Singh; Ugochukwu J. Anyaneji; Monika Moir; Stephanie van Wyk; Derek Tshiabuila; Yajna Ramphal; Arisha Maharaj; Sergei Pond; Alexander G Lucaci; Steven Weaver; Maciej F Boni; Koen Deforche; Kathleen Subramoney; Diana Hardie; Gert Marais; Deelan Doolabh; Rageema Joseph; Nokuzola Mbhele; Luicer Olubayo; Arash Iranzadeh; Alexander E Zarebski; Joseph Tsui; Moritz UG Kraemer; Oliver G Pybus; Dominique Goedhals; Phillip Armand Bester; Martin M Nyaga; Peter N Mwangi; Allison Glass; Florette Treurnicht; Marietjie Venter; Jinal N. Bhiman; Anne von Gottberg; Tulio de Oliveira.
Preprint em Inglês | medRxiv | ID: ppmedrxiv-21268028

RESUMO

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic in southern Africa has been characterised by three distinct waves. The first was associated with a mix of SARS-CoV-2 lineages, whilst the second and third waves were driven by the Beta and Delta variants respectively1-3. In November 2021, genomic surveillance teams in South Africa and Botswana detected a new SARS-CoV-2 variant associated with a rapid resurgence of infections in Gauteng Province, South Africa. Within three days of the first genome being uploaded, it was designated a variant of concern (Omicron) by the World Health Organization and, within three weeks, had been identified in 87 countries. The Omicron variant is exceptional for carrying over 30 mutations in the spike glycoprotein, predicted to influence antibody neutralization and spike function4. Here, we describe the genomic profile and early transmission dynamics of Omicron, highlighting the rapid spread in regions with high levels of population immunity.

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