Motivation
The emergence of a novel strain of betacoronavirus, SARS-CoV-2, has led to a pandemic that has been associated with over 700 000 deaths as of August 5, 2020. Research is ongoing around the ...world to create vaccines and therapies to minimize rates of disease spread and mortality. Crucial to these efforts are molecular characterizations of neutralizing antibodies to SARS-CoV-2. Such antibodies would be valuable for measuring vaccine efficacy, diagnosing exposure and developing effective biotherapeutics. Here, we describe our new database, CoV-AbDab, which already contains data on over 1400 published/patented antibodies and nanobodies known to bind to at least one betacoronavirus. This database is the first consolidation of antibodies known to bind SARS-CoV-2 as well as other betacoronaviruses such as SARS-CoV-1 and MERS-CoV. It contains relevant metadata including evidence of cross-neutralization, antibody/nanobody origin, full variable domain sequence (where available) and germline assignments, epitope region, links to relevant PDB entries, homology models and source literature.
Results
On August 5, 2020, CoV-AbDab referenced sequence information on 1402 anti-coronavirus antibodies and nanobodies, spanning 66 papers and 21 patents. Of these, 1131 bind to SARS-CoV-2.
Availabilityand implementation
CoV-AbDab is free to access and download without registration at http://opig.stats.ox.ac.uk/webapps/coronavirus. Community submissions are encouraged.
Supplementary information
Supplementary data are available at Bioinformatics online.
Too much to know Blair, Ann
2010, 20101130, 2010-11-02, 20100101
eBook, Book
The flood of information brought to us by advancing technology is often accompanied by a distressing sense of "information overload," yet this experience is not unique to modern times. In fact, says ...Ann M. Blair in this intriguing book, the invention of the printing press and the ensuing abundance of books provoked sixteenth- and seventeenth-century European scholars to register complaints very similar to our own. Blair examines methods of information management in ancient and medieval Europe as well as the Islamic world and China, then focuses particular attention on the organization, composition, and reception of Latin reference books in print in early modern Europe. She explores in detail the sophisticated and sometimes idiosyncratic techniques that scholars and readers developed in an era of new technology and exploding information.
Abstract Motivation Nanopore sequencing current signal data can be ‘basecalled’ into sequence information or analysed directly, with the capacity to identify diverse molecular features, such as ...DNA/RNA base modifications and secondary structures. However, raw signal data is large and complex, and there is a need for improved visualisation strategies to facilitate signal analysis, exploration and tool development. Results Squigualiser (Squiggle visualiser) is a toolkit for intuitive, interactive visualisation of sequence-aligned signal data, which currently supports both DNA and RNA sequencing data from Oxford Nanopore Technologies (ONT) instruments. Squigualiser is compatible with a wide range of alternative signal-alignment software packages and enables visualisation of both signal-to-read and signal-to-reference aligned data at single-base resolution. Squigualiser generates an interactive signal browser view (HTML file), in which the user can navigate across a genome/transcriptome region and customise the display. Multiple independent reads are integrated into a ‘signal pileup’ format and different datasets can be displayed as parallel tracks. Although other methods exist, Squigualiser provides the community with a software package purpose-built for raw signal data visualisation, incorporating a range of new and existing features into a unified platform. Availability Squigualiser is an open source package under an MIT licence: Https://github.com/hiruna72/squigualiser. The software was developed using Python 3.8 and can be installed with pip or bioconda or executed directly using prebuilt binaries provided with each release. Supplementary information Squigualiser usage, implementation and underlying methods development are outlined in detail in the Supplementary Notes 1–5.
Abstract Motivation Mendelian randomization (MR) is a widely used approach to estimate causal effect of variation in gene expression on complex traits. Among several MR-based algorithms, ...transcriptome-wide summary statistics-based Mendelian Randomization approach (TWMR) enables the uses of multiple SNPs as instruments and multiple gene expression traits as exposures to facilitate causal inference in observational studies. Results Here we present a Python-based implementation of TWMR and revTWMR. Our implementation offers GPU computational support for faster computations and robust computation mode resilient to highly correlated gene expressions and genetic variants Availability PyTWMR is available at github.com/soreshkov/pyTWMR Contact Sergey.Oreshkov@chuv.ch; Federico.Santoni@chuv.ch Supplementary information Supplementary data are available at Bioinformatics online.
Abstract Summary Deep mutational scanning (DMS) experiments provide a powerful method to measure the functional effects of genetic mutations at massive scales. However, the data generated from these ...experiments can be difficult to analyze, with significant variation between experimental replicates. To overcome this challenge, we developed popDMS, a computational method based on population genetics theory, to infer the functional effects of mutations from DMS data. Through extensive tests, we found that the functional effects of single mutations and epistasis inferred by popDMS are highly consistent across replicates, comparing favorably with existing methods. Our approach is flexible and can be widely applied to DMS data that includes multiple time points, multiple replicates, and different experimental conditions. Availability and Implementation PopDMS is implemented in Python and Julia, and is freely available on GitHub at https://github.com/bartonlab/popDMS. Supplementary information Supplementary data are available at Bioinformatics online.
Abstract Motivation Long-read RNA sequencing enables the mapping of RNA modifications, structures, and protein-interaction sites at the resolution of individual transcript isoforms. To understand the ...functions of these RNA features, it is critical to analyze them in the context of transcriptomic and genomic annotations, such as open reading frames and splice junctions. Results We have developed R2Dtool, a bioinformatics tool that integrates transcript-mapped information with transcript and genome annotations, allowing for the isoform-resolved analytics and graphical representation of RNA features in their genomic context. We illustrate R2Dtool’s capability to integrate and expedite RNA feature analysis using epitranscriptomics data. R2Dtool facilitates the comprehensive analysis and interpretation of alternative transcript isoforms. Availability R2Dtool is freely available under the MIT license at github.com/comprna/R2Dtool. Supplementary information Supplementary data available at https://doi.org/10.6084/m9.figshare.25730082.v1.
Abstract Motivation Engineering high-affinity binders targeting specific antigenic determinants remains a challenging and often daunting task, requiring extensive experimental screening. ...Computational methods have the potential to accelerate this process, reducing costs and time, but only if they demonstrate broad applicability and efficiency in exploring mutations, evaluating affinity, and pruning unproductive mutation paths. Results In response to these challenges, we introduce a new computational platform for optimizing protein binders towards their targets. The platform is organized as a series of modules, performing mutation selection and application, molecular dynamics (MD) simulations to sample conformations around interaction poses, and mutation prioritization using suitable scoring functions. Notably, the platform supports parallel exploration of different mutation streams, enabling in silico high-throughput screening on HPC systems. Furthermore, the platform is highly customizable, allowing users to implement their own protocols. Availability and implementation The source code is available at https://github.com/pgbarletta/locuaz and documentation is at https://locuaz.readthedocs.io/ Supplementary information Available at https://github.com/pgbarletta/suppl_info_locuaz
Abstract Motivation The Galaxy application is a popular open-source framework for data intensive sciences, counting thousands of monthly users across more than 100 public servers. To support a ...growing number of users and a greater variety of use cases, the complexity of a production-grade Galaxy installation has also grown, requiring more administration effort. There is a need for a rapid and reproducible Galaxy deployment method that can be maintained at high-availability with minimal maintenance. Results We describe the Galaxy Helm chart that codifies all elements of a production-grade Galaxy installation into a single package. Deployable on Kubernetes clusters, the chart encapsulates supporting software services and implements the best-practices model for running Galaxy. It is also the most rapid method available for deploying a scalable, production-grade Galaxy instance on one’s own infrastructure. The chart is highly configurable, allowing systems administrators to swap dependent services if desired. Notable uses of the chart include on-demand, fully-automated deployments on AnVIL, providing training infrastructure for the Bioconductor project, and as the AWS-recommended solution for running Galaxy on the Amazon cloud. Availability The source code for Galaxy Helm is available at https://github.com/galaxyproject/galaxy-helm, the corresponding Helm package at https://github.com/CloudVE/helm-charts, and the required Galaxy container image https://github.com/galaxyproject/galaxy-docker-k8s. Supplementary information Supplementary data are available at Bioinformatics online.
Abstract Summary The tidyCoverage R package provides a framework for intuitive investigation of collections of genomic tracks over genomic features, relying on the principle of tidy data ...manipulation. It defines two data structures, CoverageExperiment and AggregatedCoverage classes, directly extending the SummarizedExperiment fundamental class, and introduces a principled approach to exploring genome-wide data. This infrastructure facilitates the extraction and manipulation of genomic coverage track data across individual or multiple sets of thousands of genomic loci. This allows the end user to rapidly visualize track coverage at individual genomic loci or aggregated coverage profiles over sets of genomic loci. tidyCoverage seamlessly combines with the existing Bioconductor ecosystem to accelerate the integration of genome-wide track data in epigenomic analysis workflows. tidyCoverage emerges as a valuable tool, contributing to the advancement of epigenomics research by promoting consistency, reproducibility, and accessibility in data analysis. Availability and implementation tidyCoverage is an R package freely available from Bioconductor ≥ 3.19 (https://www.bioconductor.org/packages/tidyCoverage) for R ≥ 4.4. The software is distributed under the MIT License and is accompanied by example files and data.
Abstract Summary Motivated by theoretical and practical issues that arise when applying Principal component analysis (PCA) to count data, Townes et al. introduced “Poisson GLM-PCA”, a variation of ...PCA adapted to count data, as a tool for dimensionality reduction of single-cell RNA sequencing (scRNA-seq) data. However, fitting GLM-PCA is computationally challenging. Here we study this problem, and show that a simple algorithm, which we call “Alternating Poisson Regression” (APR), produces better quality fits, and in less time, than existing algorithms. APR is also memory-efficient and lends itself to parallel implementation on multi-core processors, both of which are helpful for handling large scRNA-seq datasets. We illustrate the benefits of this approach in three publicly available scRNA-seq datasets. The new algorithms are implemented in an R package, fastglmpca. Availability and implementation The fastglmpca R package is released on CRAN for Windows, macOS and Linux, and the source code is available at github.com/stephenslab/fastglmpca under the open source GPL-3 license. Scripts to reproduce the results in this paper are also available in the GitHub repository and on Zenodo.
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