Biology subjects

Taylor, J.

Publications and source records attributed to Taylor, J..

At least 73 records · Page 4Linked to original sources

bioRxiv2020

Fast Sparse-Group Lasso Method for Multi-response Cox Model with Applications to UK Biobank

We propose a Sparse-Group regularized Cox regression method to improve the prediction performance of large-scale and high-dimensional survival data with few observed events. Our approach is applicable when there is one or more other survival responses that 1. has a large number of observed events; 2. share a common set of associated predictors with the rare event response. This scenario is common in the UK Biobank (Sudlow et al. 2015) dataset where records for a large number of common and rare diseases of the same set of individuals are available. By analyzing these responses together, we hope to achieve higher prediction performance than when they are analyzed individually. To make this approach practical for large-scale data, we developed an accelerated proximal gradient optimization algorithm as well as a screening procedure inspired by Qian et al. (2019). We provide a software implementation of the proposed method and demonstrate its efficacy through simulations and applications to UK Biobank data.

bioinformatics↗

bioRxiv2020

Identification of compounds producing non-visual photosensation via TrpA1 in zebrafish

ABSTRACTTRPA1 receptors sense chemical irritants, but they do not normally respond to light. Previous studies have identified compounds that confer photosensitivity onto vertebrate TRPA1. However, the pharmacology of TRPA1-mediated non-visual photosensation remains poorly understood. To identify novel compounds that affect this process, we screened a large chemical library for compounds that increased light-elicited motor activity in larval zebrafish. We found structurally diverse hit compounds that were photoreactive and produced specific behavioral phenotypes. A subset of these compounds required functional TRPA1 to produce behavioral phenotypes in vivo. These findings provide novel prototype compounds for controlling TRPA1 with light and improve our understanding of non-visual TRPA1-mediated photosensation.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2020

A single-cell RNA-seq Training and Analysis Suite using the Galaxy Framework

BackgroundThe vast ecosystem of single-cell RNA-seq tools has until recently been plagued by an excess of diverging analysis strategies, inconsistent file formats, and compatibility issues between different software suites. The uptake of 10x Genomics datasets has begun to calm this diversity, and the bioinformatics community leans once more towards the large computing requirements and the statistically-driven methods needed to process and understand these ever-growing datasets. ResultsHere we outline several Galaxy workflows and learning resources for scRNA-seq, with the aim of providing a comprehensive analysis environment paired with a thorough user learning experience that bridges the knowledge gap between the computational methods and the underlying cell biology. The Galaxy reproducible bioinformatics framework provides tools, workflows and trainings that not only enable users to perform one-click 10x preprocessing, but also empowers them to demultiplex raw sequencing from custom tagged and full-length sequencing protocols. The downstream analysis supports a wide range of high-quality interoperable suites separated into common stages of analysis: inspection, filtering, normalization, confounder removal and clustering. The teaching resources cover an assortment of different concepts from computer science to cell biology. Access to all resources is provided at the singlecell.usegalaxy.eu portal. ConclusionsThe reproducible and training-oriented Galaxy framework provides a sustainable HPC environment for users to run flexible analyses on both 10x and alternative platforms. The tutorials from the Galaxy Training Network along with the frequent training workshops hosted by the Galaxy Community provide a means for users to learn, publish and teach scRNA-seq analysis. Key PointsO_LISingle-cell RNA-seq has stabilised towards 10x Genomics datasets. C_LIO_LIGalaxy provides rich and reproducible scRNA-seq workflows with a wide range of robust tools. C_LIO_LIThe Galaxy Training Network provides tutorials for the processing of both 10x and non-10x datasets. C_LI

bioinformatics↗

bioRxiv2020

Spatially discrete signalling niches regulate fibroblast heterogeneity in human lung cancer

Fibroblasts are functionally heterogeneous cells, capable of promoting and suppressing tumour progression. Across cancer types, the extent and cause of this phenotypic diversity remains unknown. We used single-cell RNA sequencing and multiplexed immunohistochemistry to examine fibroblast heterogeneity in human lung and non-small cell lung cancer (NSCLC) samples. This identified seven fibroblast subpopulations: including inflammatory fibroblasts and myofibroblasts (representing terminal differentiation states), quiescent fibroblasts, proto-myofibroblasts (x2) and proto-inflammatory fibroblasts (x2). Fibroblast subpopulations were variably distributed throughout tissues but accumulated at discrete niches associated with differentiation status. Bioinformatics analyses suggested TGF-{beta}1 and IL-1 as key regulators of myofibroblastic and inflammatory differentiation respectively. However, in vitro analyses showed that whilst TGF-{beta}1 stimulation in combination with increased tissue tension could induce myofibroblast marker expression, it failed to fully re-capitulate ex-vivo phenotypes. Similarly, IL-1{beta} treatment only induced upregulation of a subset of inflammatory fibroblast marker genes. In silico modelling of ligand-receptor signalling identified additional pathways and cell interactions likely to be involved in fibroblast activation, which can be examined using publicly available R shiny applications (at the following links: myofibroblast activation and inflammatory fibroblast activation). This highlighted a potential role for IL-11 and IL-6 (among other ligands) in myofibroblast and inflammatory fibroblast activation respectively. This analysis provides valuable insight into fibroblast subtypes and differentiation mechanisms in NSCLC.

cancer biology↗

bioRxiv2020

Greenhouse spatial effects detected in the barley (Hordeum vulgare L.) epigenome underlie stochasticity of DNA methylation

Environmental cues are known to alter the methylation profile of genomic DNA, and thereby change the expression of some genes. A proportion of such modifications may become adaptive by adjusting expression of stress response genes but others been shown to be highly stochastic, even under controlled conditions. The influence of environmental flux on plants adds an additional layer of complexity that has potential to confound attempts to interpret interactions between environment, methylome and plant form. We therefore adopt a positional and longitudinal approach to study progressive changes to barley DNA methylation patterns in response to salt exposure during development under greenhouse conditions. Methylation-Sensitive Amplified Polymorphism (MSAP) and phenotypic analyses of nine diverse barley varieties were grown in a randomized plot design, under two salt treatments (0 mM and 75 mM NaCl). Combining environmental, phenotypic and epigenetic data analyses, we show that at least part of the epigenetic variability, previously described as stochastic, is linked to environmental micro-variations during plant growth. Additionally, we show that differences in methylation increase with time of exposure to micro-variations in environment. We propose that subsequent epigenetic studies take into account microclimate-induced epigenetic variability.

plant biology↗

bioRxiv2020

Tissue-resident CD4+ T helper cells assist protective respiratory mucosal B and CD8+ T cell memory responses

The roles of CD4+ T helper cells (TH) in shaping localized memory B and CD8+ T cell immunity in the mucosal tissues are largely unexplored. Here, we report that lung TH cells provide local assistance for the optimal development of tissue-resident memory B (BRM) and CD8+ T (TRM) cells following the resolution of primary influenza virus infection. We identify a population of tissue-resident CD4+ TH (aka TRH) cells that co-exhibit follicular T helper (TFH) and TRM cell features and mediate local help of CD4+ T cells to B and CD8+ T cells. Optimal TRH cell formation requires lung B cells and transcription factors involved in TFH or TRM development. Further, we show that TRH cells deliver local help to B and CD8 T cells through CD40L and IL-21-dependent mechanisms. Our data have uncovered a new tissue-resident TH cell population that is specialized in assisting the development of mucosal protective B and CD8+ T cell responses in situ.

immunology↗

bioRxiv2019

Hidden dynamic signatures drive substrate selectivity in the disordered phosphoproteome

Phosphorylation sites are hyper-abundant in the disordered proteins of eukaryotes, suggesting that conformational dynamics (or heterogeneity) may play a major role in determining to what extent a kinase interacts with a particular substrate. In biophysical terms, substrate selectivity may be determined not just by the structural and chemical complementarity between the kinase and its protein substrates, but also by the free energy difference between the conformational ensembles that are recognized by the kinase and those that are not. To test this hypothesis, we developed an informatics framework based on statistical thermodynamics, which allows us to probe for dynamic contributions to phosphorylation, as evaluated by the ability to predict Ser/Thr/ Tyr phosphorylation sites in the disordered proteome. Essential to this framework is a decomposition of substrate sequence information into two types: vertical information encoding conserved kinase specificity motifs and horizontal (distributed) information encoding substrate conformational dynamics that are embedded, but often not apparent, within position specific conservation patterns. We find not only that conformational dynamics play a major role, but that they are the dominant contribution to substrate selectivity. In fact, the main substrate classifier distinguishing selectivity is the magnitude of change in compaction of the disordered chain upon phosphorylation. Thus, in addition to providing fundamental insights into the underlying mechanistic consequences of phosphorylation across the entire proteome, our approach provides a novel statistical thermodynamic strategy for partitioning any sequence-based search into contributions from direct chemical and structural complementarity and those from changes in conformational dynamics. Using this framework, we developed a high-performance open-source phosphorylation site predictor, PHOSforUS, which is freely available at https://github.com/bxlab/PHOSforUS.

biophysics↗

bioRxiv2019

Cellular life from the three domains and viruses are transcriptionally active in a hypersaline desert community

Microbial communities play essential roles in the biosphere and understanding the mechanisms underlying their functional adaptations to environmental conditions is critical for predicting their behavior. This aspect of microbiome function has not been well characterized in natural high-salt environments. To address this knowledge gap, and to build a general framework of relating the genomic and transcriptomic components in a microbiome, we performed a meta-omic survey of extremophile communities inhabiting halite (salt) nodules in the Atacama Desert. We found that the major phyla of this halophilic community have very different levels of total transcriptional activity and that different metabolic pathways were activated in their transcriptomes. We report that a novel Dolichomastix alga - the only eukaryote found in this system - was by far the most active community member. It produced the vast majority of the communitys photosynthetic transcripts despite being outnumbered by members of the Cyanobacteria. The divergence in the transcriptional landscapes of these segregated communities, compared to the relatively stable metagenomic functional potential, suggests that microbiomes in each salt nodule undergo unique transcriptional adjustments to adapt to local conditions. We also report the characterization of several previously unknown halophilic viruses, many of which exhibit transcriptional activity indicative of host infection. Originality-Significance StatementWhile the metagenomics of hypersaline environments have already led to many discoveries, the transcriptional adaptations and functions of halophilic microbial communities in natural environments remains understudied. We perform the first robust meta-omic investigation of a hypersaline desert ecosystem, linking the genomic and transcriptional elements of the community. Our analysis unexpectedly revealed that Eukaryotes may be the main primary producers in this extreme environment, despite halophilic Archaea and Bacteria dominating the biomass. We also expand on the existing known diversity of halophilic viruses and demonstrate abundance (copies per million reads) and metatranscriptomic activity (transcripts per million reads); putative hosts are shown on the right.

microbiology↗

bioRxiv2019

Systematic integration of GATA transcription factors and epigenomes via IDEAS paints the regulatory landscape of mouse hematopoietic cells

Members of the GATA family of transcription factors play key roles in the differentiation of specific cell lineages by regulating the expression of target genes. Three GATA factors play distinct roles in hematopoietic differentiation. In order to better understand how these GATA factors function to regulate genes throughout the genome, we are studying the epigenomic and transcriptional landscapes of hematopoietic cells in a model-driven, integrative fashion. We have formed the collaborative multi-lab VISION project to conduct ValIdated Systematic IntegratiON of epigenomic data in mouse and human hematopoiesis. The epigenomic data included nuclease accessibility in chromatin, CTCF occupancy, and histone H3 modifications for twenty cell types covering hematopoietic stem cells, multilineage progenitor cells, and mature cells across the blood cell lineages of mouse. The analysis used the Integrative and Discriminative Epigenome Annotation System (IDEAS), which learns all common combinations of features (epigenetic states) simultaneously in two dimensions - along chromosomes and across cell types. The result is a segmentation that effectively paints the regulatory landscape in readily interpretable views, revealing constitutively active or silent loci as well as the loci specifically induced or repressed in each stage and lineage. Nuclease accessible DNA segments in active chromatin states were designated candidate cis-regulatory elements in each cell type, providing one of the most comprehensive registries of candidate hematopoietic regulatory elements to date. Applications of VISION resources are illustrated for regulation of genes encoding GATA1, GATA2, GATA3, and Ikaros. VISION resources are freely available from our website http://usevision.org.

genomics↗

bioRxiv2019

An integrative view of the regulatory and transcriptional landscapes in mouse hematopoiesis

Thousands of epigenomic datasets have been generated in the past decade, but it is difficult for researchers to effectively utilize all the data relevant to their projects. Systematic integrative analysis can help meet this need, and the VISION project was established for ValIdated Systematic IntegratiON of epigenomic data in hematopoiesis. Here, we systematically integrated extensive data recording epigenetic features and transcriptomes from many sources, including individual laboratories and consortia, to produce a comprehensive view of the regulatory landscape of differentiating hematopoietic cell types in mouse. By employing IDEAS as our Integrative and Discriminative Epigenome Annotation System, we identified and assigned epigenetic states simultaneously along chromosomes and across cell types, precisely and comprehensively. Combining nuclease accessibility and epigenetic states produced a set of over 200,000 candidate cis-regulatory elements (cCREs) that efficiently capture enhancers and promoters. The transitions in epigenetic states of these cCREs across cell types provided insights into mechanisms of regulation, including decreases in numbers of active cCREs during differentiation of most lineages, transitions from poised to active or inactive states, and shifts in nuclease accessibility of CTCF-bound elements. Regression modeling of epigenetic states at cCREs and gene expression produced a versatile resource to improve selection of cCREs potentially regulating target genes. These resources are available from our VISION website (usevision.org) to aid research in genomics and hematopoiesis.

genomics↗

bioRxiv2019

Genome sequence of the cluster root forming white lupin

White lupin (Lupinus albus L.) is a legume that produces seeds recognized for their high protein content and good nutritional value (lowest glycemic index of all grains, high dietary fiber content, and zero gluten or starch)1-5. White lupin can form nitrogen-fixing nodules but has lost the ability to form mycorrhizal symbiosis with fungi6. Nevertheless, its root system is well adapted to poor soils: it produces cluster roots, constituted of dozens of determinate lateral roots that improve soil exploration and phosphate remobilization7. As phosphate is a limited resource that comes from rock reserves8, the production of cluster roots is a trait of interest to improve fertilizers efficiency. Using long reads sequencing technologies, we provide a high-quality genome sequence of a modern variety of white lupin (2n=50, 451 Mb), as well as de novo assemblies of a landrace and a wild relative. We describe how domestication impacted soil exploration capacity through the early establishment of lateral and cluster roots. We identify the APETALA2 transcription factor LaPUCHI-1, homolog of the Arabidopsis morphogenesis coordinator9, as a potential regulator of this trait. Our high-quality genome and companion genomic and transcriptomic resources enable the development of modern breeding strategies to increase and stabilize yield and to develop new varieties with reduced allergenic properties (caused by conglutins10), which would favor the deployment of this promising culture.

genomics↗

bioRxiv2019

Computer-assisted EEG diagnostic review for idiopathic generalized epilepsy

Epilepsy diagnosis can be costly, time-consuming and not uncommonly inaccurate. The reference standard diagnostic monitoring is continuous video-EEG monitoring, ideally capturing all events or concordant interictal discharges. Automating EEG data review would save time and resources, thus enabling more people to receive reference standard monitoring and also potentially herald a more quantitative approach to therapeutic outcomes. There is substantial research into automated detection of seizures and epileptic activity from EEG. However, automated detection software is not widely used in the clinic; and, despite numerous published algorithms, few methods have regulatory approval for detecting epileptic activity from EEG.\n\nThis study reports on a deep learning algorithm for computer-assisted EEG review. Deep, convolutional neural networks were trained to detect epileptic discharges using a pre-existing dataset of over 6000 labelled events in a cohort of 103 patients with idiopathic generalized epilepsy (IGE). Patients underwent 24-hour ambulatory outpatient EEG, and all data was curated and confirmed independently by two epilepsy specialists (Seneviratne et al, 2016). The resulting automated detection algorithm was then used to review diagnostic scalp-EEG for seven patients (four with IGE and three with events mimicking seizures) to validate performance in a clinical setting.\n\nThe automated detection algorithm showed state-of-the-art performance for detecting epileptic activity from clinical EEG, with mean sensitivity of >95% and corresponding mean false positive rate of 1 detection per minute. Importantly, diagnostic case studies showed that the automated detection algorithm reduced human review time by 80%-99%, without compromising event detection or diagnostic accuracy. The presented results demonstrate that computer-assisted review can increase the speed and accuracy of EEG assessment and has the potential to greatly improve therapeutic outcomes.

neuroscience↗

bioRxiv2019

DNA shape complements sequence-based representations of transcription factor binding sites

The position weight matrix (PWM) has long been a useful tool for describing variation in the composition of regions of DNA such as transcription factor (TF) binding sites. It is difficult, however, to relate the sequence-based representation of a DNA motif to the biological features of the interaction of a TF with its binding site. Here we present an alternative strategy for representing DNA motifs - called Structural Motif (StruM) - that can easily represent different sets of structural features. Structural features are inferred from dinucleotide properties listed in the Dinucleotide Property Database. StruMs are able to specifically model TF binding sites, using an encoding strategy that is distinct from sequence-based models. This difference in encoding strategies makes StruMs complementary to sequence-based methods of TF binding site identification.

bioinformatics↗

bioRxiv2019

Massively parallel reporter assays combined with cell-type specific eQTL informed multiple melanoma loci and identified a pleiotropic function of HIV-1 restriction gene, MX2, in melanoma promotion

Genome-wide association studies (GWAS) have identified [~]20 melanoma susceptibility loci. To identify susceptibility genes and variants simultaneously from multiple GWAS loci, we integrated massively-parallel reporter assays (MPRA) with cell type-specific epigenomic data as well as melanocyte-specific expression quantitative trait loci (eQTL) profiling. Starting from 16 melanoma loci, we selected 832 variants overlapping active regions of chromatin in cells of melanocytic lineage and identified 39 candidate functional variants displaying allelic transcriptional activity by MPRA. For four of these loci, we further identified four colocalizing melanocyte cis-eQTL genes (CTSS, CASP8, MX2, and MAFF) matching the allelic activity of MPRA functional variants. Among these, we further characterized the locus encompassing the HIV-1 restriction gene, MX2, on chromosome band Chr21q22.3 and validated a functional variant, rs398206, among multiple high LD variants. rs398206 mediates allelic transcriptional activity via binding of the transcription factor, YY1. This allelic transcriptional regulation is consistent with a significant cis-eQTL of MX2 in primary human melanocytes, where the melanoma risk-associated A allele of rs398206 is correlated with higher MX2 levels. Melanocyte-specific transgenic expression of human MX2 in a zebrafish model demonstrated accelerated melanoma formation in a BRAFV600E background. Thus, using an efficient scalable approach to streamline GWAS follow-up functional studies, we identified multiple candidate melanoma susceptibility genes and variants, and uncovered a pleiotropic function of MX2 in melanoma susceptibility.

genomics↗

bioRxiv2019

Gene-methylation interactions: Discovering region-wise DNA methylation levels that modify SNP-associated disease risk

The genetic code is tightly linked to epigenetic instructions as to what genes to express, and when and where to express them. The most studied epigenetic mark is DNA methylation at CpG dinucleotides. Todays technology enables a rapid assessment of DNA sequence and methylation levels at a single-site resolution for hundreds of thousands of sites in the human genome, in thousands of individuals at a time. Recent years have seen a rapid increase in epigenome-wide association studies (EWAS) searching for the causes of risk for genetic diseases that previous genome-wide association studies (GWAS) could not pinpoint. However, those single-omics data analyses led to even more questions and it has become clear that only by integrating data one can get closer to answers. Here, we propose two new methods within genetic association analyses that treat the level of DNA methylation at a given CpG site as environmental exposure. Our analyses search for statistical interactions between a given allele and DNA methylation (GxMe), and between a parent-of-origin effect and DNA methylation (PoOx Me). The new methods were implemented in the R package Haplin and were tested on a dataset comprising genotype data from mother-father-child triadsm with DNA methylation data from the children only. The phenotype here was orofacial clefts (OFC), a relatively common birth defect in humans, which is known to have a genetic origin and an environmental component possibly mediated by DNA methylation. We found no significant PoOxMe interactions and a few significant GxMe interactions. Our results show that the significance of these interaction effects depends on the genomic region in which the CpGs reside and on the number of strata of methylation level. We demonstrate that, by including the methylation level around the SNP in the analyses, the estimated relative risk of OFC can change significantly. We also discuss the importance of including control data in such analyses. The new methods will be of value for all the researchers who want to explore genome- and epigenome-wide datasets in an integrative manner. Moreover, thanks to the implementation in a popular R package, the methods are easily accessible and enable fast scans of the genome- and epigenome-wide datasets.

epidemiology↗

bioRxiv2019

The full-length transcriptome of C. elegans using direct RNA sequencing

Current transcriptome annotations have largely relied on short read lengths intrinsic to most widely used high-throughput cDNA sequencing technologies. For example, in the annotation of the Caenorhabditis elegans transcriptome, more than half of the transcript isoforms lack full-length support and instead rely on inference from short reads that do not span the full length of the isoform. We applied nanopore-based direct RNA sequencing to characterize the developmental polyadenylated transcriptome of C. elegans. Taking advantage of long reads spanning the full length of mRNA transcripts, we provide support for 20,902 splice isoforms across 14,115 genes, without the need for computational reconstruction of gene models. Of the isoforms identified, 2,188 are novel splice isoforms not present in the Wormbase WS265 annotation. Furthermore, we identified 16,325 3 untranslated region (3UTR) isoforms, 2,304 of which are novel and do not fall within 10 bp of existing 3UTR datasets and annotations. Combining 3UTRs and splice isoforms we identified 25,944 full-length isoforms. We also determined that poly(A) tail lengths of transcripts vary across development, as do the strengths of previously reported correlations between poly(A) tail length and expression level, and poly(A) tail length and 3UTR length. Finally, we have formatted this data as a publically accessible track hub, enabling researchers to explore this dataset easily in a genome browser.

genomics↗

bioRxiv2019

Environmental plasticity and colonisation history in the Atlantic salmon microbiome: a translocation experiment

Microbial communities associated with the gut and the skin are strongly influenced by environmental factors, and can rapidly adapt to change. Historical processes may also affect the microbiome. In particular, variation in microbial colonisation in early life has the potential to induce lasting effects on microbial assemblages. However, little is known about the relative extent of microbiome plasticity or the importance of historical colonisation effects following environmental change, especially for non-mammalian species. To investigate this we performed a reciprocal translocation of Atlantic salmon between captive and semi-natural conditions. Wild and hatchery-reared fry were transferred to three common garden experimental environments for six weeks: standard hatchery conditions, hatchery conditions with an enriched diet, and simulated wild conditions. We characterised the faecal and skin microbiome of individual fish before and after the environmental translocation, using a BACI (before-after-control-impact) design. We found evidence of extensive plasticity in both gut and skin microbiota, with the greatest changes in alpha and beta diversity associated with the largest changes in environment and diet. Microbiome richness and diversity were entirely determined by environment, with no detectable historical effects of fish origin. Microbiome structure was also strongly influenced by current environmental conditions but, for the first time in fish, we also found evidence of colonisation history, including a number of OTUs characteristic of captive rearing. These results may have important implications for host adaptation to local selective pressures, and also highlight how conditions during early life can have a long-term influence on the microbiome and, potentially, host health.

microbiology↗

bioRxiv2018

Cloud Bursting Galaxy: Federated Identity and Access Management

MotivationLarge biomedical datasets, such as those from genomics and imaging, are increasingly being stored on commercial and institutional cloud computing platforms. This is because cloud-scale computing resources, from robust backup to highspeed data transfer to scalable compute and storage, are needed to make these large datasets usable. However, one challenge for large-scale biomedical data on the cloud is providing secure access, especially when datasets are distributed across platforms. While there are open Web protocols for secure authentication and authorization, these protocols are not in wide use in bioinformatics and are difficult to use for even technologically sophisticated users.\n\nResultsWe have developed a generic and extensible approach for securely accessing biomedical datasets distributed across cloud computing platforms. Our approach combines OpenID Connect and OAuth2, best-practice Web protocols for authentication and authorization, together with Galaxy (https://galaxyproject.org), a web-based computational workbench used by thousands of scientists across the world. With our enhanced version of Galaxy, users can access and analyze data distributed across multiple cloud computing providers without any special knowledge of access/authorization protocols. Our approach does not require users to share permanent credentials (e.g., username, password, API key), instead relying on automatically-generated temporary tokens that refresh as needed. Our approach is generalizable to most identity providers and cloud computing platforms. To the best of our knowledge, Galaxy is the only computational workbench where users can access biomedical datasets across multiple cloud computing platforms using best-practice Web security approaches and thereby minimize risks of unauthorized data access and credential use.\n\nAvailability and ImplementationFreely available for academic and commercial use under the open-source Academic Free License (https://opensource.org/licenses/AFL-3.0) from the following Github repositories: https://github.com/galaxyproject/galaxy and https://github.com/galaxyproject/cloudauthz\n\nContactjalili@ohsu.edu, goecksj@ohsu.edu

bioinformatics↗