IQ-TREE (http://www.iqtree.org, last accessed February 6, 2020) is a user-friendly and widely used software package for phylogenetic inference using maximum likelihood. Since the release of version 1 in 2014, we have continuously expanded IQ-TREE to integrate a plethora of new models of sequence evolution and efficient computational approaches of phylogenetic inference to deal with genomic data. Here, we describe notable features of IQ-TREE version 2 and highlight the key advantages over other software.

https://openresearch-repository.anu.edu.au/bitstream/1885/212335/1/01_Bui_IQ-TREE_2%253A_New_Models_and_2020.pdf

IQ-TREE 2: New Models and Efficient Methods for Phylogenetic Inference in the Genomic Era.

Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus.

SARS-CoV-2 Receptor ACE2 Is an Interferon-Stimulated Gene in Human Airway Epithelial Cells and Is Detected in Specific Cell Subsets across Tissues.

http://diposit.ub.edu/dspace/bitstream/2445/165519/4/L20_2020_Cell_181_905_OA.pdf

Inhibition of SARS-CoV-2 Infections in Engineered Human Tissues Using Clinical-Grade Soluble Human ACE2.

The SARS-CoV-2 B.1.617 lineage was identified in October 2020 in India1–5. Since then, it has become dominant in some regions of India and in the UK, and has spread to many other countries6. The lineage includes three main subtypes (B1.617.1, B.1.617.2 and B.1.617.3), which contain diverse mutations in the N-terminal domain (NTD) and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein that may increase the immune evasion potential of these variants. B.1.617.2—also termed the Delta variant—is believed to spread faster than other variants. Here we isolated an infectious strain of the Delta variant from an individual with COVID-19 who had returned to France from India. We examined the sensitivity of this strain to monoclonal antibodies and to antibodies present in sera from individuals who had recovered from COVID-19 (hereafter referred to as convalescent individuals) or who had received a COVID-19 vaccine, and then compared this strain with other strains of SARS-CoV-2. The Delta variant was resistant to neutralization by some anti-NTD and anti-RBD monoclonal antibodies, including bamlanivimab, and these antibodies showed impaired binding to the spike protein. Sera collected from convalescent individuals up to 12 months after the onset of symptoms were fourfold less potent against the Delta variant relative to the Alpha variant (B.1.1.7). Sera from individuals who had received one dose of the Pfizer or the AstraZeneca vaccine had a barely discernible inhibitory effect on the Delta variant. Administration of two doses of the vaccine generated a neutralizing response in 95% of individuals, with titres three- to fivefold lower against the Delta variant than against the Alpha variant. Thus, the spread of the Delta variant is associated with an escape from antibodies that target non-RBD and RBD epitopes of the spike protein. The SARS-CoV-2 Delta variant partially evades neutralization by several monoclonal antibodies and by sera from individuals who have had COVID-19, but two doses of anti-COVID-19 vaccines still generate a strong neutralizing response.

/pdf/reduced-sensitivity-of-sars-cov-2-variant-delta-to-antibody-4vfjtit4rl.pdf

Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization.

Summary Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualization platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, open to health professionals, epidemiologists, virologists and the public alike. Availability and implementation All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.

/pdf/nextstrain-real-time-tracking-of-pathogen-evolution-1vkingd0mr.pdf

Nextstrain: real-time tracking of pathogen evolution.

Quickly and flexibly exploring high-dimensional datasets, such as scRNAseq data, is underserved but critical for hypothesis generation, dataset annotation, publication, sharing, and community reuse cellxgene is a highly generalizable, web-based interface for exploring high dimensional datasets along categorical, continuous and spatial dimensions, as well as feature annotation cellxgene is differentiated by its ability to performantly handle millions of observations, and bridges a critical gap by enabling computational and experimental biologists to iteratively ask questions of private and public datasets In doing so, cellxgene increases the utility and reusability of datasets across the single-cell ecosystem The codebase can be accessed at https://githubcom/chanzuckerberg/cellxgene For questions and inquiries, please contact cellxgene@chanzuckerbergcom

/pdf/cellxgene-a-performant-scalable-exploration-platform-for-182983i0pf.pdf

cellxgene: a performant, scalable exploration platform for high dimensional sparse matrices

Summary : Understanding the spread and evolution of pathogens is important for effective public health measures and surveillance. Nextstrain consists of a database of viral genomes, a bioinformatics pipeline for phylodynamics analysis, and an interactive visualisation platform. Together these present a real-time view into the evolution and spread of a range of viral pathogens of high public health importance. The visualization integrates sequence data with other data types such as geographic information, serology, or host species. Nextstrain compiles our current understanding into a single accessible location, publicly available for use by health professionals, epidemiologists, virologists and the public alike.
 Availability and implementation : All code (predominantly JavaScript and Python) is freely available from github.com/nextstrain and the web-application is available at nextstrain.org.

https://www.biorxiv.org/content/early/2017/11/22/224048.full.pdf

Nextstrain: real-time tracking of pathogen evolution

chanzuckerberg/cellxgene: Release 0.15.0

Systems for large scale deliberation have resolved polarized issues and shifted agenda setting into the public's hands. These systems integrate bridging-based ranking algorithms - including group informed consensus implemented in Polis and the continuous matrix factorization approach implemented by Twitter Birdwatch - making it possible to highlight statements which enjoy broad support from a diversity of opinion groups. Polis has been productively employed to foster more constructive political deliberation at nation scale in law making exercises. Twitter Birdwatch is implemented with the intention of addressing misinformation in the global public square. From one perspective, Twitter Birdwatch can be viewed as an anti-misinformation system which has deliberative aspects. But it can also be viewed as a first step towards a generalized deliberative system, using Twitter's misinformation problem as a proving ground. In this paper, we propose that Twitter could adapt Birdwatch to produce maps of public opinion. We describe a system in five parts for generalizing Birdwatch: activation of a deliberative system and topic selection, population sampling and the role of expert networks, deliberation, reporting interpretable results and finally distribution of the results to the public and those in power.

Colin Megill

Papers

Nextstrain: real-time tracking of pathogen evolution.

cellxgene: a performant, scalable exploration platform for high dimensional sparse matrices

Nextstrain: real-time tracking of pathogen evolution

chanzuckerberg/cellxgene: Release 0.15.0

"Coherent Mode" for the World's Public Square