Software
Software and tools developed by CViSB
The CViSB Data Portal provides access to all datasets and patient metadata generated or curated by the Center for Viral Systems Biology, which studies Ebola, Lassa Fever, and COVID-19.
funded by: NIAID
Floki is a tool under active development that can be used to visualize and interpret metagenomic data using the hierarchical taxonomy structure. It can be used to identify and filter out contaminants. It can also be used to visualize batch effects by grouping multiple samples together. Annotations from other sources at every taxon level can be combined with sequencing results to narrow down the search space for taxons of interest.
funded by: NIAID
iVar is a computational package that contains functions broadly useful for viral amplicon-based sequencing. Additional tools for metagenomic sequencing are actively being incorporated into iVar. While each of these functions can be accomplished using existing tools, iVar contains an intersection of functionality from multiple tools that are required to call iSNVs and consensus sequences from viral sequencing data across multiple replicates. We implemented the following functions in iVar: (1) trimming of primers and low-quality bases, (2) consensus calling, (3) variant calling - both iSNVs and insertions/deletions, and (4) identifying mismatches to primer sequences and excluding the corresponding reads from alignment files. An amplicon-based sequencing framework for accurately measuring intrahost virus diversity using PrimalSeq and iVar, Genome Biology 2019 20:8 Nathan D Grubaugh, Karthik Gangavarapu, Joshua Quick, Nathaniel L Matteson, Jaqueline Goes De Jesus, Bradley J Main, Amanda L Tan, Lauren M Paul, Doug E Brackney, Saran Grewal, Nikos Gurfield, Koen KA Van Rompay, Sharon Isern, Scott F Michael, Lark L Coffey, Nicholas J Loman, Kristian G Andersen bioRxiv doi: https://doi.org/10.1101/383513
funded by: NIAID
license: GNU GPL v3
In response to the current outbreak of SARS-CoV-2 (the virus that causes COVID-19), researchers worldwide have been generating and openly sharing data, publications, reagents, code, protocols, and more. Broad sharing of these resources improves the speed and efficiency of science. Unfortunately, there are no uniform standards and repositories for collecting all this information in one place. Outbreak.info aggregates data across scientific sources, providing tools to meet three major aims: (1) Track trends in COVID-19 cases and deaths, (2) Track daily developments in SARS-CoV-2 variants, and (3) Integrate publications, preprints, clinical trials, datasets, protocols, and other resources into one searchable library of COVID-19 research
funded by: NIAID
license: GNU GPL v3
An application programming interface (API) that enables programmatic access to data available on outbreak.info
funded by: NIAID
license: GNU GPL v3
A suite of miscellaneous tools that can be used to: 1) generate information for large-scale genomic surveillance of SARS-CoV-2 sequences. This functionality relies on external tools such as datafunk, minimap2, and pandas. 2) prepare results and data files from SARS-CoV-2 sequencing analysis for release to public databases such as GISAID, Google Cloud, and GitHub
funded by: NIAID
license: GNU GPL v3
An R package that acts as a convenient client to the outbreak.info API.
funded by: NIAID
license: GNU GPL v3
BEAST is a cross-platform program for Bayesian analysis of molecular sequences using MCMC. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. We include a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.
funded by: European Union Seventh Framework Programme for research, technological development and demonstration European Union Seventh Framework Programme for research, technological development and demonstration Wellcome Trust NSF NIH NIH NIAID
license: LGPL v3
RBeast is an R package for working with output files from BEAST and BEAST2. This package consists of four main functions: (1) Use beautier to create BEAST2 input (.xml) files. (2) Use beastier to run BEAST2. (3) Use tracerer to parse BEAST2 output (.log, .trees, etc) files. (4) Use BEASTmasteR for tip-dating analyses using fossils as dated terminal taxa.
funded by: NSF NIAID
license: MIT
BEAGLE is a high-performance library that can perform the core calculations at the heart of most Bayesian and Maximum Likelihood phylogenetics packages. It can make use of highly-parallel processors such as those in graphics cards (GPUs) found in many PCs. The project involves an open API and fast implementations of a library for evaluating phylogenetic likelihoods (continuous time Markov processes) of biomolecular sequence evolution. The aim is to provide high performance evaluation ‘services’ to a wide range of phylogenetic software, both Bayesian samplers and Maximum Likelihood optimizers. This allows these packages to make use of implementations that make use of optimized hardware such as graphics processing units.
funded by: NFS NFS NFS NFS NFS NIH NIH NIAID Wellcome Trust European Research Council
license: LGPL v3
Tracer is a software package for visualising and analysing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualisation, demographic trajectory reconstruction, conditional posterior distribution summary and more. Tracer can read output files from MrBayes, BEAST, BEAST2, RevBayes, Migrate, LAMARC and and possibly other MCMC programs from other domains.
funded by: NIAID
Python
funded by: NIAID
Python
funded by: NIAID
Python
funded by: NIAID
This package of tools, named Single Cell Analysis of B cells (scab), is part of the broader ab[x] toolkit for antibody sequence and repertoire analysis and comprises three primary functions: 1) integration of single cell RNA-seq, AgBCs and natively-paired adaptive immune receptor sequence data; 2) provide a means for identifying antigen-positive cells from AgBC data using a probabilistic classifier; and 3) exploration and visualization of data-rich single cell profiles
funded by: NIAID