scholarly journals DeepNano-blitz: a fast base caller for MinION nanopore sequencers

2020 ◽  
Vol 36 (14) ◽  
pp. 4191-4192 ◽  
Author(s):  
Vladimír Boža ◽  
Peter Perešíni ◽  
Broňa Brejová ◽  
Tomáš Vinař
Keyword(s):  
Detailed Analysis ◽  
Real Time ◽  
Species Identification ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Human Pathogen ◽  
Human Dna ◽  
Oxford Nanopore ◽  
Sample Composition ◽  
Analyze Data

Abstract Motivation Oxford Nanopore MinION is a portable DNA sequencer that is marketed as a device that can be deployed anywhere. Current base callers, however, require a powerful GPU to analyze data produced by MinION in real time, which hampers field applications. Results We have developed a fast base caller DeepNano-blitz that can analyze stream from up to two MinION runs in real time using a common laptop CPU (i7-7700HQ), with no GPU requirements. The base caller settings allow trading accuracy for speed and the results can be used for real time run monitoring (i.e. sample composition, barcode balance, species identification, etc.) or prefiltering of results for more detailed analysis (i.e. filtering out human DNA from human–pathogen runs). Availability and implementation DeepNano-blitz has been developed and tested on Linux and Intel processors and is available under MIT license at https://github.com/fmfi-compbio/deepnano-blitz. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals DeepNano-blitz: A Fast Base Caller for MinION Nanopore Sequencers

2020 ◽  
Author(s):  
Vladimír Boža ◽  
Peter Perešíni ◽  
Broňa Brejová ◽  
Tomáš Vinař
Keyword(s):  
Detailed Analysis ◽  
Real Time ◽  
Species Identification ◽  
Human Pathogen ◽  
Link Type ◽  
Human Dna ◽  
Oxford Nanopore ◽  
Sample Composition ◽  
Analyze Data ◽  
Dna Sequencer

AbstractMotivationOxford Nanopore MinION is a portable DNA sequencer that is marketed as a device that can be deployed anywhere. Current base callers, however, require a powerful GPU to analyze data produced by MinION in real time, which hampers field applications.ResultsWe have developed a fast base caller DeepNano-blitz that can analyze stream from up to two MinION runs in real time using a common laptop CPU (i7-7700HQ), with no GPU requirements. The base caller settings allow trading accuracy for speed and the results can be used for real time run monitoring (i.e. sample composition, barcode balance, species identification, etc.) or pre-filtering of results for more detailed analysis (i.e. filtering out human DNA from human–pathogen runs).Availability and ImplementationDeepNano-blitz has been developed and tested on Linux and is available under MIT license at https://github.com/fmfi-compbio/[email protected]

scholarly journals What's in my pot? Real-time species identification on the MinION

2015 ◽  
Author(s):  
Sissel Juul ◽  
Fernando Izquierdo ◽  
Adam Hurst ◽  
Xiaoguang Dai ◽  
Amber Wright ◽  
...  
Keyword(s):  
Real Time ◽  
Species Identification ◽  
Sequence Data ◽  
Fixed Time ◽  
Oxford Nanopore ◽  
Sample Composition ◽  
Bioinformatics Application ◽  
Analysis Workflow ◽  
Quantitative Manner ◽  
Oxford Nanopore Technologies

Whole genome sequencing on next-generation instruments provides an unbiased way to identify the organisms present in complex metagenomic samples. However, the time-to-result can be protracted because of fixed-time sequencing runs and cumbersome bioinformatics workflows. This limits the utility of the approach in settings where rapid species identification is crucial, such as in the quality control of food-chain components, or in during an outbreak of an infectious disease. Here we present What′s in my Pot? (WIMP), a laboratory and analysis workflow in which, starting with an unprocessed sample, sequence data is generated and bacteria, viruses and fungi present in the sample are classified to subspecies and strain level in a quantitative manner, without prior knowledge of the sample composition, in approximately 3.5 hours. This workflow relies on the combination of Oxford Nanopore Technologies′ MinION ™ sensing device with a real-time species identification bioinformatics application.

scholarly journals SiLiCO: A Simulator of Long Read Sequencing in PacBio and Oxford Nanopore

2016 ◽  
Author(s):  
Ethan Alexander García Baker ◽  
Sara Goodwin ◽  
W. Richard McCombie ◽  
Olivia Mendivil Ramos
Keyword(s):  
Reference Data ◽  
Supplementary Information ◽  
Data Sets ◽  
Simulation Tool ◽  
Supplementary Data ◽  
Structural Variants ◽  
Oxford Nanopore ◽  
Long Read ◽  
Sequencing Platforms ◽  
Core Facilities

AbstractSummaryLong read sequencing platforms, which include the widely used Pacific Biosciences (PacBio) platform and the emerging Oxford Nanopore platform, aim to produce sequence fragments in excess of 15-20 kilobases, and have proved advantageous in the identification of structural variants and easing genome assembly. However, long read sequencing remains relatively expensive and error prone, and failed sequencing runs represent a significant problem for genomics core facilities. To quantitatively assess the underlying mechanics of sequencing failure, it is essential to have highly reproducible and controllable reference data sets to which sequencing results can be compared. Here, we present SiLiCO, the first in silico simulation tool to generate standardized sequencing results from both of the leading long read sequencing platforms.AvailabilitySiLiCO is an open source package written in Python. It is freely available at https://www.github.com/ethanagbaker/SiLiCO under the GNU GPL 3.0 license.Contact<emails>Supplementary informationSupplementary data are available at Bioinformatics online.

scholarly journals ccNetViz: a WebGL-based JavaScript library for visualization of large networks

2020 ◽  
Vol 36 (16) ◽  
pp. 4527-4529
Author(s):  
Ales Saska ◽  
David Tichy ◽  
Robert Moore ◽  
Achilles Rasquinha ◽  
Caner Akdas ◽  
...  
Keyword(s):  
Systems Biology ◽  
Complex Networks ◽  
Open Source ◽  
High Speed ◽  
A Priori ◽  
Supplementary Information ◽  
Network Visualization ◽  
Supplementary Data ◽  
Web Based ◽  
Flow Of Information

Abstract Summary Visualizing a network provides a concise and practical understanding of the information it represents. Open-source web-based libraries help accelerate the creation of biologically based networks and their use. ccNetViz is an open-source, high speed and lightweight JavaScript library for visualization of large and complex networks. It implements customization and analytical features for easy network interpretation. These features include edge and node animations, which illustrate the flow of information through a network as well as node statistics. Properties can be defined a priori or dynamically imported from models and simulations. ccNetViz is thus a network visualization library particularly suited for systems biology. Availability and implementation The ccNetViz library, demos and documentation are freely available at http://helikarlab.github.io/ccNetViz/. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Epidemiological modeling in StochSS Live!

2021 ◽  
Author(s):  
Richard Jiang ◽  
Bruno Jacob ◽  
Matthew Geiger ◽  
Sean Matthew ◽  
Bryan Rumsey ◽  
...  
Keyword(s):  
Stochastic Model ◽  
Epidemiological Model ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Web Based ◽  
Epidemiological Modeling ◽  
Modeling Simulation ◽  
Wide Range ◽  
Biochemical Systems

Abstract Summary We present StochSS Live!, a web-based service for modeling, simulation and analysis of a wide range of mathematical, biological and biochemical systems. Using an epidemiological model of COVID-19, we demonstrate the power of StochSS Live! to enable researchers to quickly develop a deterministic or a discrete stochastic model, infer its parameters and analyze the results. Availability and implementation StochSS Live! is freely available at https://live.stochss.org/ Supplementary information Supplementary data are available at Bioinformatics online.

KEC: unique sequence search by K-mer exclusion

2021 ◽  
Author(s):  
Pavel Beran ◽  
Dagmar Stehlíková ◽  
Stephen P Cohen ◽  
Vladislav Čurn
Keyword(s):  
Amino Acid ◽  
Nucleic Acid ◽  
Source Code ◽  
Unique Sequence ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Laptop Computers ◽  
Sequence Search ◽  
Target Sequences ◽  
Cross Reference

Abstract Summary Searching for amino acid or nucleic acid sequences unique to one organism may be challenging depending on size of the available datasets. K-mer elimination by cross-reference (KEC) allows users to quickly and easily find unique sequences by providing target and non-target sequences. Due to its speed, it can be used for datasets of genomic size and can be run on desktop or laptop computers with modest specifications. Availability and implementation KEC is freely available for non-commercial purposes. Source code and executable binary files compiled for Linux, Mac and Windows can be downloaded from https://github.com/berybox/KEC. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals CorGAT: a tool for the functional annotation of SARS-CoV-2 genomes

2020 ◽  
Author(s):  
Matteo Chiara ◽  
Federico Zambelli ◽  
Marco Antonio Tangaro ◽  
Pietro Mandreoli ◽  
David S Horner ◽  
...  
Keyword(s):  
Functional Annotation ◽  
Ad Hoc ◽  
State Of The Art ◽  
Supplementary Information ◽  
Genomic Sequences ◽  
Supplementary Data ◽  
Evolutionary Patterns ◽  
Genomic Variants ◽  
Art Methods ◽  
Available Resources

Abstract Summary While over 200 000 genomic sequences are currently available through dedicated repositories, ad hoc methods for the functional annotation of SARS-CoV-2 genomes do not harness all currently available resources for the annotation of functionally relevant genomic sites. Here, we present CorGAT, a novel tool for the functional annotation of SARS-CoV-2 genomic variants. By comparisons with other state of the art methods we demonstrate that, by providing a more comprehensive and rich annotation, our method can facilitate the identification of evolutionary patterns in the genome of SARS-CoV-2. Availabilityand implementation Galaxy   http://corgat.cloud.ba.infn.it/galaxy; software: https://github.com/matteo14c/CorGAT/tree/Revision_V1; docker: https://hub.docker.com/r/laniakeacloud/galaxy_corgat. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals UniBioDicts: Unified access to Biological Dictionaries

2020 ◽  
Author(s):  
John Zobolas ◽  
Vasundra Touré ◽  
Martin Kuiper ◽  
Steven Vercruysse
Keyword(s):  
User Interface ◽  
Life Science ◽  
Biological Data ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Query Interface ◽  
Controlled Vocabularies ◽  
Search String ◽  
Software Packages ◽  
The Right

Abstract Summary We present a set of software packages that provide uniform access to diverse biological vocabulary resources that are instrumental for current biocuration efforts and tools. The Unified Biological Dictionaries (UniBioDicts or UBDs) provide a single query-interface for accessing the online API services of leading biological data providers. Given a search string, UBDs return a list of matching term, identifier and metadata units from databases (e.g. UniProt), controlled vocabularies (e.g. PSI-MI) and ontologies (e.g. GO, via BioPortal). This functionality can be connected to input fields (user-interface components) that offer autocomplete lookup for these dictionaries. UBDs create a unified gateway for accessing life science concepts, helping curators find annotation terms across resources (based on descriptive metadata and unambiguous identifiers), and helping data users search and retrieve the right query terms. Availability and implementation The UBDs are available through npm and the code is available in the GitHub organisation UniBioDicts (https://github.com/UniBioDicts) under the Affero GPL license. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals CONCUR: quick and robust calculation of codon usage from ribosome profiling data

2020 ◽  
Author(s):  
Michaela Frye ◽  
Susanne Bornelöv
Keyword(s):  
Codon Usage ◽  
Ribosome Profiling ◽  
Supplementary Information ◽  
Supplementary Data ◽  
Usage Analysis

Abstract Summary CONCUR is a standalone tool for codon usage analysis in ribosome profiling experiments. CONCUR uses the aligned reads in BAM format to estimate codon counts at the ribosome E-, P- and A-sites and at flanking positions. Availability and implementation CONCUR is written in Perl and is freely available at https://github.com/susbo/concur. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals MorphOT: transport-based interpolation between EM maps with UCSF ChimeraX

2020 ◽  
Author(s):  
Arthur Ecoffet ◽  
Frédéric Poitevin ◽  
Khanh Dao Duc
Keyword(s):  
Optimal Transport ◽  
Three Dimensional ◽  
Linear Interpolation ◽  
The Other ◽  
Supplementary Information ◽  
Conformational Heterogeneity ◽  
Supplementary Data ◽  
Image Dataset ◽  
Standard Linear ◽  
Unique Potential

Abstract Motivation Cryogenic electron microscopy (cryo-EM) offers the unique potential to capture conformational heterogeneity, by solving multiple three-dimensional classes that co-exist within a single cryo-EM image dataset. To investigate the extent and implications of such heterogeneity, we propose to use an optimal-transport-based metric to interpolate barycenters between EM maps and produce morphing trajectories. Results While standard linear interpolation mostly fails to produce realistic transitions, our method yields continuous trajectories that displace densities to morph one map into the other, instead of blending them. Availability and implementation Our method is implemented as a plug-in for ChimeraX called MorphOT, which allows the use of both CPU or GPU resources. The code is publicly available on GitHub (https://github.com/kdd-ubc/MorphOT.git), with documentation containing tutorial and datasets. Supplementary information Supplementary data are available at Bioinformatics online.

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