An international virtual hackathon to build tools for the analysis of structural variants within species ranging from coronaviruses to vertebrates

In October 2020, 62 scientists from nine nations worked together remotely in the Second Baylor College of Medicine & DNAnexus hackathon, focusing on different related topics on Structural Variation, Pan-genomes, and SARS-CoV-2 related research. The overarching focus was to assess the current status of the field and identify the remaining challenges. Furthermore, how to combine the strengths of the different interests to drive research and method development forward. Over the four days, eight groups each designed and developed new open-source methods to improve the identification and analysis of variations among species, including humans and SARS-CoV-2. These included improvements in SV calling, genotyping, annotations and filtering. Together with advancements in benchmarking existing methods. Furthermore, groups focused on the diversity of SARS-CoV-2. Daily discussion summary and methods are available publicly at https://github.com/collaborativebioinformatics provides valuable insights for both participants and the research community.

Download Full-text

An international virtual hackathon to build tools for the analysis of structural variants within species ranging from coronaviruses to vertebrates

F1000Research ◽

10.12688/f1000research.51477.2 ◽

2021 ◽

Vol 10 ◽

pp. 246

Author(s):

Ann M. Mc Cartney ◽

Medhat Mahmoud ◽

Michael Jochum ◽

Daniel Paiva Agustinho ◽

Barry Zorman ◽

...

Keyword(s):

Open Source ◽

Structural Variation ◽

Method Development ◽

Research Community ◽

Current Status ◽

Baylor College ◽

Structural Variants ◽

Related Research ◽

Link Type

Download Full-text

RaGOO: fast and accurate reference-guided scaffolding of draft genomes

Genome Biology ◽

10.1186/s13059-019-1829-6 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 56

Author(s):

Michael Alonge ◽

Sebastian Soyk ◽

Srividya Ramakrishnan ◽

Xingang Wang ◽

Sara Goodwin ◽

...

Keyword(s):

Arabidopsis Thaliana ◽

Open Source ◽

Genome Analysis ◽

De Novo ◽

Structural Variants ◽

Tomato Genome ◽

Pan Genome ◽

Link Type ◽

Genome Assemblies

Abstract We present RaGOO, a reference-guided contig ordering and orienting tool that leverages the speed and sensitivity of Minimap2 to accurately achieve chromosome-scale assemblies in minutes. After the pseudomolecules are constructed, RaGOO identifies structural variants, including those spanning sequencing gaps. We show that RaGOO accurately orders and orients 3 de novo tomato genome assemblies, including the widely used M82 reference cultivar. We then demonstrate the scalability and utility of RaGOO with a pan-genome analysis of 103 Arabidopsis thaliana accessions by examining the structural variants detected in the newly assembled pseudomolecules. RaGOO is available open source at https://github.com/malonge/RaGOO.

Download Full-text

The 2016 Bioinformatics Open Source Conference (BOSC)

F1000Research ◽

10.12688/f1000research.9663.1 ◽

2016 ◽

Vol 5 ◽

pp. 2464

Author(s):

Nomi L. Harris ◽

Peter J.A. Cock ◽

Brad Chapman ◽

Christopher J. Fields ◽

Karsten Hokamp ◽

...

Keyword(s):

Software Development ◽

Open Source ◽

Open Source Software ◽

Open Science ◽

Research Community ◽

Biological Research ◽

Non Profit ◽

Link Type ◽

Bioinformatics Software ◽

Bioinformatics Community

Message from the ISCB: The Bioinformatics Open Source Conference (BOSC) is a yearly meeting organized by the Open Bioinformatics Foundation (OBF), a non-profit group dedicated to promoting the practice and philosophy of Open Source software development and Open Science within the biological research community. BOSC has been run since 2000 as a two-day Special Interest Group (SIG) before the annual ISMB conference. The 17th annual BOSC (http://www.open-bio.org/wiki/BOSC_2016) took place in Orlando, Florida in July 2016. As in previous years, the conference was preceded by a two-day collaborative coding event open to the bioinformatics community. The conference brought together nearly 100 bioinformatics researchers, developers and users of open source software to interact and share ideas about standards, bioinformatics software development, and open and reproducible science.

Download Full-text

Learning Analytics Considered Harmful

Online Learning ◽

10.24059/olj.v16i3.272 ◽

2012 ◽

Vol 16 (3) ◽

Cited By ~ 3

Author(s):

Laurie P Dringus

Keyword(s):

Big Data ◽

Online Learning ◽

Learning Analytics ◽

Online Courses ◽

Research Community ◽

Current Status ◽

Online Course ◽

Full Potential

This essay is written to present a prospective stance on how learning analytics, as a core evaluative approach, must help instructors uncover the important trends and evidence of quality learner data in the online course. A critique is presented of strategic and tactical issues of learning analytics. The approach to the critique is taken through the lens of questioning the current status of applying learning analytics to online courses. The goal of the discussion is twofold: (1) to inform online learning practitioners (e.g., instructors and administrators) of the potential of learning analytics in online courses and (2) to broaden discussion in the research community about the advancement of learning analytics in online learning. In recognizing the full potential of formalizing big data in online coures, the community must address this issue also in the context of the potentially "harmful" application of learning analytics.

Download Full-text

Open source tools for geographic analysis in transport planning

Journal of Geographical Systems ◽

10.1007/s10109-020-00342-2 ◽

2021 ◽

Author(s):

Robin Lovelace

Keyword(s):

User Interface ◽

Open Source ◽

Citizen Participation ◽

Simulation Software ◽

First Century ◽

Transport Planning ◽

Geographic Analysis ◽

Link Type ◽

Twenty First Century ◽

Interactive Map

AbstractGeographic analysis has long supported transport plans that are appropriate to local contexts. Many incumbent ‘tools of the trade’ are proprietary and were developed to support growth in motor traffic, limiting their utility for transport planners who have been tasked with twenty-first century objectives such as enabling citizen participation, reducing pollution, and increasing levels of physical activity by getting more people walking and cycling. Geographic techniques—such as route analysis, network editing, localised impact assessment and interactive map visualisation—have great potential to support modern transport planning priorities. The aim of this paper is to explore emerging open source tools for geographic analysis in transport planning, with reference to the literature and a review of open source tools that are already being used. A key finding is that a growing number of options exist, challenging the current landscape of proprietary tools. These can be classified as command-line interface, graphical user interface or web-based user interface tools and by the framework in which they were implemented, with numerous tools released as R, Python and JavaScript packages, and QGIS plugins. The review found a diverse and rapidly evolving ‘ecosystem’ tools, with 25 tools that were designed for geographic analysis to support transport planning outlined in terms of their popularity and functionality based on online documentation. They ranged in size from single-purpose tools such as the QGIS plugin AwaP to sophisticated stand-alone multi-modal traffic simulation software such as MATSim, SUMO and Veins. Building on their ability to re-use the most effective components from other open source projects, developers of open source transport planning tools can avoid ‘reinventing the wheel’ and focus on innovation, the ‘gamified’ A/B Street https://github.com/dabreegster/abstreet/#abstreet simulation software, based on OpenStreetMap, a case in point. The paper, the source code of which can be found at https://github.com/robinlovelace/open-gat, concludes that, although many of the tools reviewed are still evolving and further research is needed to understand their relative strengths and barriers to uptake, open source tools for geographic analysis in transport planning already hold great potential to help generate the strategic visions of change and evidence that is needed by transport planners in the twenty-first century.

Download Full-text

stLFRsv: A Germline Structural Variant Analysis Pipeline Using Co-barcoded Reads

Frontiers in Genetics ◽

10.3389/fgene.2021.636239 ◽

2021 ◽

Vol 12 ◽

Author(s):

Junfu Guo ◽

Chang Shi ◽

Xi Chen ◽

Ou Wang ◽

Ping Liu ◽

...

Keyword(s):

Structural Variation ◽

Signal To Noise Ratio ◽

Recall Rate ◽

Structural Variants ◽

Analysis Pipeline ◽

Haplotype Phasing ◽

Base Level ◽

Long Reads ◽

Variant Analysis ◽

Complex Structural

Co-barcoded reads originating from long DNA fragments (mean length >30 kbp) maintain both single base level accuracy and long-range genomic information. We propose a pipeline, stLFRsv, to detect structural variation using co-barcoded reads. stLFRsv identifies abnormal large gaps between co-barcoded reads to detect potential breakpoints and reconstruct complex structural variants (SVs). Haplotype phasing by co-barcoded reads increases the signal to noise ratio, and barcode sharing profiles are used to filter out false positives. We integrate the short read SV caller smoove for smaller variants with stLFRsv. The integrated pipeline was evaluated on the well-characterized genome HG002/NA24385, and 74.5% precision and a 22.4% recall rate were obtained for deletions. stLFRsv revealed some large variants not included in the benchmark set that were verified by long reads or assembly. For the HG001/NA12878 genome, stLFRsv also achieved the best performance for both resource usage and the detection of large variants. Our work indicates that co-barcoded read technology has the potential to improve genome completeness.

Download Full-text

Generating Property-Matched Decoy Molecules Using Deep Learning

10.1101/2020.08.26.268193 ◽

2020 ◽

Author(s):

Fergus Imrie ◽

Anthony R. Bradley ◽

Charlotte M. Deane

Keyword(s):

Deep Learning ◽

Virtual Screening ◽

Method Development ◽

Screening Method ◽

Screening Methods ◽

Additional Risk ◽

Link Type ◽

Screening Performance ◽

And Training ◽

Virtual Screening Performance

An essential step in the development of virtual screening methods is the use of established sets of actives and decoys for benchmarking and training. However, the decoy molecules in commonly used sets are biased meaning that methods often exploit these biases to separate actives and decoys, rather than learning how to perform molecular recognition. This fundamental issue prevents generalisation and hinders virtual screening method development. We have developed a deep learning method (DeepCoy) that generates decoys to a user’s preferred specification in order to remove such biases or construct sets with a defined bias. We validated DeepCoy using two established benchmarks, DUD-E and DEKOIS 2.0. For all DUD-E targets and 80 of the 81 DEKOIS 2.0 targets, our generated decoy molecules more closely matched the active molecules’ physicochemical properties while introducing no discernible additional risk of false negatives. The DeepCoy decoys improved the Deviation from Optimal Embedding (DOE) score by an average of 81% and 66%, respectively, decreasing from 0.163 to 0.032 for DUD-E and from 0.109 to 0.038 for DEKOIS 2.0. Further, the generated decoys are harder to distinguish than the original decoy molecules via docking with Autodock Vina, with virtual screening performance falling from an AUC ROC of 0.71 to 0.63. The code is available at https://github.com/oxpig/DeepCoy. Generated molecules can be downloaded from http://opig.stats.ox.ac.uk/resources.

Download Full-text

chewBBACA: A complete suite for gene-by-gene schema creation and strain identification

10.1101/173146 ◽

2017 ◽

Cited By ~ 5

Author(s):

Mickael Silva ◽

Miguel Machado ◽

Diogo N. Silva ◽

Mirko Rossi ◽

Jacob Moran-Gilad ◽

...

Keyword(s):

Open Source ◽

Core Genome ◽

Bacterial Species ◽

Outbreak Detection ◽

Strain Identification ◽

List Type ◽

Whole Genome ◽

Link Type ◽

The Creation ◽

Allele Calling

ABSTRACTGene-by-gene approaches are becoming increasingly popular in bacterial genomic epidemiology and outbreak detection. However, there is a lack of open-source scalable software for schema definition and allele calling for these methodologies. The chewBBACA suite was designed to assist users in the creation and evaluation of novel whole-genome or core-genome gene-by-gene typing schemas and subsequent allele calling in bacterial strains of interest. The software can run in a laptop or in high performance clusters making it useful for both small laboratories and large reference centers. ChewBBACA is available athttps://github.com/B-UMMI/chewBBACAor as a docker image athttps://hub.docker.com/r/ummidock/chewbbaca/.DATA SUMMARYAssembled genomes used for the tutorial were downloaded from NCBI in August 2016 by selecting those submitted asStreptococcus agalactiaetaxon or sub-taxa. All the assemblies have been deposited as a zip file in FigShare (https://figshare.com/s/9cbe1d422805db54cd52), where a file with the original ftp link for each NCBI directory is also available.Code for the chewBBACA suite is available athttps://github.com/B-UMMI/chewBBACAwhile the tutorial example is found athttps://github.com/B-UMMI/chewBBACA_tutorial.I/We confirm all supporting data, code and protocols have been provided within the article or through supplementary data files. ⊠IMPACT STATEMENTThe chewBBACA software offers a computational solution for the creation, evaluation and use of whole genome (wg) and core genome (cg) multilocus sequence typing (MLST) schemas. It allows researchers to develop wg/cgMLST schemes for any bacterial species from a set of genomes of interest. The alleles identified by chewBBACA correspond to potential coding sequences, possibly offering insights into the correspondence between the genetic variability identified and phenotypic variability. The software performs allele calling in a matter of seconds to minutes per strain in a laptop but is easily scalable for the analysis of large datasets of hundreds of thousands of strains using multiprocessing options. The chewBBACA software thus provides an efficient and freely available open source solution for gene-by-gene methods. Moreover, the ability to perform these tasks locally is desirable when the submission of raw data to a central repository or web services is hindered by data protection policies or ethical or legal concerns.

Download Full-text

The Popgen Pipeline Platform: A Software Platform for Facilitating Population Genomic Analyses

10.1101/785774 ◽

2019 ◽

Author(s):

Andrew Webb ◽

Jared Knoblauch ◽

Nitesh Sabankar ◽

Apeksha Sukesh Kallur ◽

Jody Hey ◽

...

Keyword(s):

Open Source ◽

Development Time ◽

End Users ◽

File Format ◽

Software Platform ◽

Format Conversion ◽

Link Type ◽

Population Genomic ◽

Genomic Analyses ◽

File Format Conversion

AbstractHere we present the Pop-Gen Pipeline Platform (PPP), a software platform with the goal of reducing the computational expertise required for conducting population genomic analyses. The PPP was designed as a collection of scripts that facilitate common population genomic workflows in a consistent and standardized Python environment. Functions were developed to encompass entire workflows, including: input preparation, file format conversion, various population genomic analyses, output generation, and visualization. By facilitating entire workflows, the PPP offers several benefits to prospective end users - it reduces the need of redundant in-house software and scripts that would require development time and may be error-prone, or incorrect. The platform has also been developed with reproducibility and extensibility of analyses in mind. The PPP is an open-source package that is available for download and use at https://ppp.readthedocs.io/en/latest/PPP_pages/install.html

Download Full-text

Reflections on Research in Kinesiology

Kinesiology Review ◽

10.1123/kr.2021-0031 ◽

2021 ◽

pp. 1-7

Author(s):

Karl M. Newell

Keyword(s):

Physical Activity ◽

Research Agenda ◽

Healthy Lifestyle ◽

Human Movement ◽

Current Status ◽

Special Issue ◽

New Developments ◽

Related Research ◽

Research And Teaching ◽

Initial Research

This paper provides reflections on the progress to date and current status of research in kinesiology. The accompanying overview articles in this special issue of Kinesiology Review show that the contemporary disciplinary/professional foci of kinesiology remain, by and large, the same as the initial research and teaching structures of 50 years ago, as outlined in the inaugural overviews. Nevertheless, within this prevailing disciplinary/professional structure, there have been many new developments in movement-related research, including the juxtaposition of novel alignments and integrations of certain specializations of kinesiology. There is general consensus that the quality and quantity of research in kinesiology have advanced substantially, albeit unevenly, on multiple fronts, both within and between the areas of specialization. The research agenda in kinesiology has benefitted from the growing realization of the centrality of human movement and physical activity in contributing to a healthy lifestyle for individuals and societies.

Download Full-text