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2. User-friendly, scalable tools and workflows for single-cell RNA-seq analysis

Author

Moreno, Pablo, Huang, Ni, Manning, Jonathan R., Mohammed, Suhaib, Solovyev, Andrey, Polanski, Krzysztof, Bacon, Wendi, Chazarra, Ruben, Talavera-López, Carlos, Doyle, Maria A., Marnier, Guilhem, Grüning, Björn, Rasche, Helena, George, Nancy, Fexova, Silvie Korena, Alibi, Mohamed, Miao, Zhichao, Perez-Riverol, Yasset, Haeussler, Maximilian, Brazma, Alvis, Teichmann, Sarah, Meyer, Kerstin B., and Papatheodorou, Irene

Published
2021
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3. Galaxy Training: A Powerful Framework for Teaching!

Author

Hiltemann, Saskia, Rasche, Helena, Gladman, Simon, Hotz, Hans-Rudolf, Larivière, Delphine, Blankenberg, Daniel, Jagtap, Pratik D., Wollmann, Thomas, Bretaudeau, Anthony, Goué, Nadia, Griffin, Timothy J., Royaux, Coline, Le Bras, Yvan, Mehta, Subina, Syme, Anna, Coppens, Frederik, Droesbeke, Bert, Soranzo, Nicola, Bacon, Wendi, Psomopoulos, Fotis, Gallardo-Alba, Cristóbal, Davis, John, Föll, Melanie Christine, Fahrner, Matthias, Doyle, Maria A., Serrano-Solano, Beatriz, Fouilloux, Anne Claire, van Heusden, Peter, Maier, Wolfgang, Clements, Dave, Heyl, Florian, on behalf of the Galaxy Training Network, [ missing ], Grüning, Björn, Batut, Bérénice, Erasmus University Medical Center [Rotterdam] (Erasmus MC), Albert-Ludwigs-Universität Freiburg, University of Melbourne, Friedrich Miescher Institute for Biomedical Research (FMI), Novartis Research Foundation, Pennsylvania State University (Penn State), Penn State System, Department of Genomic Medicine [Lerner Research Institute, Cleveland Clinic], Lerner Research Institute [Cleveland, OH, USA], Cleveland Clinic-Cleveland Clinic, University of Minnesota [Twin Cities] (UMN), University of Minnesota System, Heidelberg University, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Plateforme bioinformatique GenOuest [Rennes], Université de Rennes (UR)-Plateforme Génomique Santé Biogenouest®-Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Université Clermont Auvergne (UCA), Muséum National d' Histoire Naturelle [Concarneau], Universiteit Gent = Ghent University (UGENT), Earlham Institute [Norwich], The Open University [Milton Keynes] (OU), Centre for Research and Technology Hellas (CERTH), Johns Hopkins University (JHU), University of Freiburg [Freiburg], Simula Research Laboratory [Lysaker] (SRL), South African National Bioinformatics Institute (SANBI), University of the Western Cape (UWC), Anaconda, Inc. [Austin], Plateforme Auvergne Bioinformatique (AuBi), Mésocentre Clermont Auvergne, Université Clermont Auvergne (UCA)-Université Clermont Auvergne (UCA), and Pathology

Subjects
Cellular and Molecular Neuroscience, Computational Theory and Mathematics, Ecology, Modeling and Simulation, Genetics, Biology and Life Sciences, ONLINE, STUDENTS, Molecular Biology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Ecology, Evolution, Behavior and Systematics
Abstract

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments.

Published
2023

5. Training Infrastructure as a Service

Author

Rasche, Helena, primary, Hyde, Cameron, additional, Davis, John, additional, Gladman, Simon, additional, Coraor, Nate, additional, Bretaudeau, Anthony, additional, Cuccuru, Gianmauro, additional, Bacon, Wendi, additional, Serrano-Solano, Beatriz, additional, Hillman-Jackson, Jennifer, additional, Hiltemann, Saskia, additional, Zhou, Miaomiao, additional, Grüning, Björn, additional, and Stubbs, Andrew, additional

Published
2022
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7. Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses

Author

Bacon, Wendi, Holinski, Alexandra, Pujol, Marina, Wilmott, Meredith, Morgan, Sarah L, and on behalf of the European Molecular Biology Laboratory—European Bioinformatics Institute Training Team

Subjects
Cellular and Molecular Neuroscience, Computational Theory and Mathematics, Ecology, Modeling and Simulation, Genetics, Computational Biology, Molecular Biology, Ecology, Evolution, Behavior and Systematics
Published
2022

8. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update

Author

Afgan, Enis, Nekrutenko, Anton, Grüning, Bjórn, Blankenberg, Daniel, Goecks, Jeremy, Schatz, Michael, Ostrovsky, Alexander, Mahmoud, Alexandru, Lonie, Andrew, Syme, Anna, Fouilloux, Anne, Bretaudeau, Anthony, Kumar, Anup, Eschenlauer, Arthur, Desanto, Assunta, Guerler, Aysam, Serrano-Solano, Beatriz, Batut, Bérénice, Grüning, Björn, Langhorst, Bradley, Carr, Bridget, Raubenolt, Bryan, Hyde, Cameron, Bromhead, Catherine, Barnett, Christopher, Royaux, Coline, Gallardo, Cristóbal, Fornika, Daniel, Baker, Dannon, Bouvier, Dave, Clements, Dave, de Lima Morais, David, Tabernero, David Lopez, Lariviere, Delphine, Nasr, Engy, Zambelli, Federico, Heyl, Florian, Psomopoulos, Fotis, Coppens, Frederik, Price, Gareth, Cuccuru, Gianmauro, Corguillé, Gildas Le, von Kuster, Greg, Akbulut, Gulsum Gudukbay, Rasche, Helena, Hotz, Hans-Rudolf, Eguinoa, Ignacio, Makunin, Igor, Ranawaka, Isuru, Taylor, James, Joshi, Jayadev, Hillman-Jackson, Jennifer, Chilton, John, Kamali, Kaivan, Suderman, Keith, Poterlowicz, Krzysztof, Yvan, Le Bras, Lopez-Delisle, Lucille, Sargent, Luke, Bassetti, Madeline, Tangaro, Marco Antonio, van den Beek, Marius, Čech, Martin, Bernt, Matthias, Fahrner, Matthias, Tekman, Mehmet, Föll, Melanie, Crusoe, Michael, Roncoroni, Miguel, Kucher, Natalie, Coraor, Nate, Stoler, Nicholas, Rhodes, Nick, Soranzo, Nicola, Pinter, Niko, Goonasekera, Nuwan, Moreno, Pablo, Videm, Pavankumar, Melanie, Petera, Mandreoli, Pietro, Jagtap, Pratik, Gu, Qiang, Weber, Ralf, Lazarus, Ross, Vorderman, Ruben, Hiltemann, Saskia, Golitsynskiy, Sergey, Garg, Shilpa, Bray, Simon, Gladman, Simon, Leo, Simone, Mehta, Subina, Griffin, Timothy, Jalili, Vahid, Yves, Vandenbrouck, Wen, Victor, Nagampalli, Vijay, Bacon, Wendi, de Koning, Willem, Maier, Wolfgang, Briggs, Peter, Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Pathology, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)

Subjects
[SDV]Life Sciences [q-bio], Genetics, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology
Abstract

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations. Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

Published
2022

9. Deciphering Tumour Microenvironment of Liver Cancer through Deconvolution of Bulk RNA-Seq Data with Single-Cell Atlas.

Author

Zhang, Shaoshi, Bacon, Wendi, Peppelenbosch, Maikel P., van Kemenade, Folkert, and Stubbs, Andrew Peter

Subjects
*LIVER tumors, *SEQUENCE analysis, *CELL physiology, *RNA, *MICROARRAY technology, *GENE expression profiling, *PATHOLOGIC neovascularization, *CELL lines, *ALGORITHMS
Abstract

Simple Summary: ScRNA-seq is a powerful tool for investigating the cancer microenvironment, but the cost of analysing every scientific scenario is prohibitive. Fortunately, deconvolution of bulk RNA-seq data with scRNA-seq cell atlas reference datasets provides a cheaper strategy. In this study, we validated the feasibility of deciphering the microenvironment of liver cancer through the estimation of cell fractions with Cibersortx and scRNA-seq atlas reference datasets. Five cell types are associated with patient outcomes, showing that deconvolution is a useful method for characterising the tumour microenvironment. Liver cancers give rise to a heavy burden on healthcare worldwide. Understanding the tumour microenvironment (TME) underpins the development of precision therapy. Single-cell RNA sequencing (scRNA-seq) technology has generated high-quality cell atlases of the TME, but its wider application faces enormous costs for various clinical circumstances. Fortunately, a variety of deconvolution algorithms can instead repurpose bulk RNA-seq data, alleviating the need for generating scRNA-seq datasets. In this study, we reviewed major public omics databases for relevance in this study and utilised eight RNA-seqs and one microarray dataset from clinical studies. To decipher the TME of liver cancer, we estimated the fractions of liver cell components by deconvoluting the samples with Cibersortx using three reference scRNA-seq atlases. We also confirmed that Cibersortx can accurately deconvolute cell types/subtypes of interest. Compared with non-tumorous liver, liver cancers showed multiple decreased cell types forming normal liver microarchitecture, as well as elevated cell types involved in fibrogenesis, abnormal angiogenesis, and disturbed immune responses. Survival analysis shows that the fractions of five cell types/subtypes significantly correlated with patient outcomes, indicating potential therapeutic targets. Therefore, deconvolution of bulk RNA-seq data with scRNA-seq atlas references can be a useful tool to help understand the TME. [ABSTRACT FROM AUTHOR]

Published
2023
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10. Training Infrastructure as a Service.

Author

Rasche, Helena, Hyde, Cameron, Davis, John, Gladman, Simon, Coraor, Nate, Bretaudeau, Anthony, Cuccuru, Gianmauro, Bacon, Wendi, Serrano-Solano, Beatriz, Hillman-Jackson, Jennifer, Hiltemann, Saskia, Zhou, Miaomiao, Grüning, Björn, and Stubbs, Andrew

Subjects
INFRASTRUCTURE (Economics), ACHIEVEMENT gains (Education), PHYSIOLOGY education
Abstract

Background Hands-on training, whether in bioinformatics or other domains, often requires significant technical resources and knowledge to set up and run. Instructors must have access to powerful compute infrastructure that can support resource-intensive jobs running efficiently. Often this is achieved using a private server where there is no contention for the queue. However, this places a significant prerequisite knowledge or labor barrier for instructors, who must spend time coordinating deployment and management of compute resources. Furthermore, with the increase of virtual and hybrid teaching, where learners are located in separate physical locations, it is difficult to track student progress as efficiently as during in-person courses. Findings Originally developed by Galaxy Europe and the Gallantries project, together with the Galaxy community, we have created Training Infrastructure-as-a-Service (TIaaS), aimed at providing user-friendly training infrastructure to the global training community. TIaaS provides dedicated training resources for Galaxy-based courses and events. Event organizers register their course, after which trainees are transparently placed in a private queue on the compute infrastructure, which ensures jobs complete quickly, even when the main queue is experiencing high wait times. A built-in dashboard allows instructors to monitor student progress. Conclusions TIaaS provides a significant improvement for instructors and learners, as well as infrastructure administrators. The instructor dashboard makes remote events not only possible but also easy. Students experience continuity of learning, as all training happens on Galaxy, which they can continue to use after the event. In the past 60 months, 504 training events with over 24,000 learners have used this infrastructure for Galaxy training. [ABSTRACT FROM AUTHOR]

Published
2023
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11. Applications of single-cell RNA sequencing in drug discovery and development

Author

Van de Sande, Bram, Lee, Joon Sang, Mutasa-Gottgens, Euphemia, Naughton, Bart, Bacon, Wendi, Manning, Jonathan, Wang, Yong, Pollard, Jack, Mendez, Melissa, Hill, Jon, Kumar, Namit, Cao, Xiaohong, Chen, Xiao, Khaladkar, Mugdha, Wen, Ji, Leach, Andrew, and Ferran, Edgardo

Abstract

Single-cell technologies, particularly single-cell RNA sequencing (scRNA-seq) methods, together with associated computational tools and the growing availability of public data resources, are transforming drug discovery and development. New opportunities are emerging in target identification owing to improved disease understanding through cell subtyping, and highly multiplexed functional genomics screens incorporating scRNA-seq are enhancing target credentialling and prioritization. ScRNA-seq is also aiding the selection of relevant preclinical disease models and providing new insights into drug mechanisms of action. In clinical development, scRNA-seq can inform decision-making via improved biomarker identification for patient stratification and more precise monitoring of drug response and disease progression. Here, we illustrate how scRNA-seq methods are being applied in key steps in drug discovery and development, and discuss ongoing challenges for their implementation in the pharmaceutical industry.

Published
2023
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15. Mll-AF4 Confers Enhanced Self-Renewal and Lymphoid Potential during a Restricted Window in Development

Author

Barrett, Neil A, Malouf, Camille, Kapeni, Chrysa, Bacon, Wendi A, Giotopoulos, George, Jacobsen, Sten Eirik W, Huntly, Brian J, Ottersbach, Katrin, Giotopoulos, George [0000-0003-1390-6592], Huntly, Brian [0000-0003-0312-161X], and Apollo - University of Cambridge Repository

Subjects
Leukemia, Lymphoma, B-Cell, Oncogene Proteins, Fusion, Mice, Transgenic, Article, Mice, lcsh:Biology (General), Precursor B-Cell Lymphoblastic Leukemia-Lymphoma, hemic and lymphatic diseases, Animals, Lymphocytes, Cell Self Renewal, lcsh:QH301-705.5, Myeloid-Lymphoid Leukemia Protein
Abstract

Summary MLL-AF4+ infant B cell acute lymphoblastic leukemia is characterized by an early onset and dismal survival. It initiates before birth, and very little is known about the early stages of the disease’s development. Using a conditional Mll-AF4-expressing mouse model in which fusion expression is targeted to the earliest definitive hematopoietic cells generated in the mouse embryo, we demonstrate that Mll-AF4 imparts enhanced B lymphoid potential and increases repopulation and self-renewal capacity during a putative pre-leukemic state. This occurs between embryonic days 12 and 14 and manifests itself most strongly in the lymphoid-primed multipotent progenitor population, thus pointing to a window of opportunity and a potential cell of origin. However, this state alone is insufficient to generate disease, with the mice succumbing to B cell lymphomas only after a long latency. Future analysis of the molecular details of this pre-leukemic state will shed light on additional events required for progression to acute leukemia., Graphical Abstract, Highlights • Mll-AF4 confers enhanced B cell potential and causes an expansion of pro-B cells • Mll-AF4 increases self-renewal potential • Mll-AF4 exerts its effects in a restricted developmental window • The LMPP is a potential cell of origin for Mll-AF4-associated disease, Barrett et al. describe the changes in pre-natal hematopoiesis induced by the Mll-AF4 oncogene in vivo. These include enhanced B lymphoid potential, an expansion of pro-B cells, and increased self-renewal. The authors identify the midgestation lymphoid-primed multipotent progenitor as a potential cell of origin.

Published
2016

16. Analysis of Jak2 signaling reveals resistance of mouse embryonic hematopoietic stem cells to myeloproliferative disease mutation

Author

Mascarenhas, Maria I, Bacon, Wendi A, Kapeni, Chrysa, Fitch, Simon R, Kimber, Gillian, Cheng, SW Priscilla, Li, Juan, Green, Anthony R, Ottersbach, Katrin, Ottersbach, Katrin [0000-0002-6880-4895], and Apollo - University of Cambridge Repository

Subjects
Mice, Knockout, Mice, Phosphatidylinositol 3-Kinases, Myeloproliferative Disorders, Amino Acid Substitution, Mutation, Missense, Animals, Cytokines, Janus Kinase 2, Embryo, Mammalian, Hematopoietic Stem Cells, DNA Damage, Signal Transduction
Abstract

The regulation of hematopoietic stem cell (HSC) emergence during development provides important information about the basic mechanisms of blood stem cell generation, expansion, and migration. We set out to investigate the role that cytokine signaling pathways play in these early processes and show here that the 2 cytokines interleukin 3 and thrombopoietin have the ability to expand hematopoietic stem and progenitor numbers by regulating their survival and proliferation. For this, they differentially use the Janus kinase (Jak2) and phosphatidylinositol 3-kinase (Pi3k) signaling pathways, with Jak2 mainly relaying the proproliferation signaling, whereas Pi3k mediates the survival signal. Furthermore, using Jak2-deficient embryos, we demonstrate that Jak2 is crucially required for the function of the first HSCs, whereas progenitors are less dependent on Jak2. The JAK2V617F mutation, which renders JAK2 constitutively active and has been linked to myeloproliferative neoplasms, was recently shown to compromise adult HSC function, negatively affecting their repopulation and self-renewal ability, partly through the accumulation of JAK2V617F-induced DNA damage. We report here that nascent HSCs are resistant to the JAK2V617F mutation and show no decrease in repopulation or self-renewal and no increase in DNA damage, even in the presence of 2 mutant copies. More importantly, this unique property of embryonic HSCs is stably maintained through ≥1 round of successive transplantations. In summary, our dissection of cytokine signaling in embryonic HSCs has uncovered unique properties of these cells that are of clinical importance.

Published
2016

18. Efficacy and safety of high-dose chemotherapy with autologous stem cell transplantation in senior versus younger adults with newly diagnosed multiple myeloma

Author

Huang, Li-Wen, primary, Bacon, Wendi, additional, Cirrincione, Constance, additional, Peterson, Bercedis, additional, Long, Gwynn, additional, Rizzieri, David, additional, Sullivan, Keith M., additional, Corbet, Kelly, additional, Horwitz, Mitchell, additional, Chao, Nelson, additional, Gasparetto, Cristina, additional, and Tuchman, Sascha A., additional

Published
2017
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19. Efficacy of Autologous Stem Cell Transplantation in Older Multiple Myeloma Patients

Author

Huang, Li-Wen, primary, Bacon, Wendi, additional, Cirrincione, Constance, additional, Peterson, Bercedis, additional, Long, Gwynn D., additional, Rizzieri, David A., additional, Horwitz, Mitchell E., additional, Sullivan, Keith, additional, Corbet, Kelly, additional, Chao, Nelson J., additional, Gasparetto, Cristina, additional, and Tuchman, Sascha, additional

Published
2016
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22. Cyclophosphamide-based hematopoietic stem cell mobilization before autologous stem cell transplantation in newly diagnosed multiple myeloma

Author

Tuchman, Sascha A, primary, Bacon, Wendi A, additional, Huang, Li-Wen, additional, Long, Gwynn, additional, Rizzieri, David, additional, Horwitz, Mitchell, additional, Chute, John P., additional, Sullivan, Keith, additional, Morris Engemann, Ashley, additional, Yopp, Amanda, additional, Li, Zhiguo, additional, Corbet, Kelly, additional, Chao, Nelson, additional, and Gasparetto, Cristina, additional

Published
2014
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23. Correction: Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses.

Author

Bacon, Wendi, Holinski, Alexandra, Pujol, Marina, Wilmott, Meredith, and Morgan, Sarah L

Subjects
*BIOINFORMATICS, *HEBBIAN memory, *ROTENONE
Abstract

Reference 1 Bacon W, Holinski A, Pujol M, Wilmott M, Morgan SL, on behalf of the European Molecular Biology Laboratory - European Bioinformatics Institute Training Team (2022) Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses. The Acknowledgments section contains spelling errors. [Extracted from the article]

Published
2023
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25. Mll-AF4 Confers Enhanced Self-Renewal and Lymphoid Potential during a Restricted Window in Development.

Author

Barrett, Neil A., Malouf, Camille, Kapeni, Chrysa, Bacon, Wendi A., Giotopoulos, George, Jacobsen, Sten Eirik W., Huntly, Brian J., and Ottersbach, Katrin

Abstract

Summary MLL-AF4+ infant B cell acute lymphoblastic leukemia is characterized by an early onset and dismal survival. It initiates before birth, and very little is known about the early stages of the disease’s development. Using a conditional Mll-AF4-expressing mouse model in which fusion expression is targeted to the earliest definitive hematopoietic cells generated in the mouse embryo, we demonstrate that Mll-AF4 imparts enhanced B lymphoid potential and increases repopulation and self-renewal capacity during a putative pre-leukemic state. This occurs between embryonic days 12 and 14 and manifests itself most strongly in the lymphoid-primed multipotent progenitor population, thus pointing to a window of opportunity and a potential cell of origin. However, this state alone is insufficient to generate disease, with the mice succumbing to B cell lymphomas only after a long latency. Future analysis of the molecular details of this pre-leukemic state will shed light on additional events required for progression to acute leukemia. [ABSTRACT FROM AUTHOR]

Published
2016
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26. High Dose BCNU/Melphalan Preparative Regimen Doubles Event Free Survival of Myeloma Patients Undergoing Autologous Transplantation

Author

Gasparetto, Cristina, primary, Bacon, Wendi A., additional, Doan, Phuong, additional, Rizzieri, David A., additional, Horwitz, Mitchell E., additional, Chute, John P., additional, Sullivan, Keith M., additional, Yopp, Amanda, additional, Li, Zhiguo, additional, Chao, Nelson J., additional, and Long, Gwynn D., additional

Published
2011
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28. Measurement of Heterogeneous Reaction Rates: Three Strategies for Controlling Mass Transport and Their Application to Indium-Mediated Allylations

Author

Olson, Isabel A., primary, Bacon, Wendi A., additional, Baez Sosa, Yessica Y., additional, Delaney, Katherine M., additional, Forte, Salvador A., additional, Guglielmo, Michael A., additional, Hill, Alexa N., additional, Kiesow, Katrina H., additional, Langenbacher, Rachel E., additional, Xun, Yuhan, additional, Young, Ryan O., additional, and Bowyer, Walter J., additional

Published
2011
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29. The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update

Author

Ostrovsky, Alexander E., Mahmoud, Alexandru, Lonie, Andrew J., Syme, Anna, Fouilloux, Anne, Bretaudeau, Anthony, Nekrutenko, Anton, Kumar, Anup, Eschenlauer, Arthur C., DeSanto, Assunta D., Guerler, Aysam, Serrano-Solano, Beatriz, Batut, Berenice, Gruening, Bjoern A., Langhorst, Bradley W., Carr, Bridget, Raubenolt, Bryan A., Hyde, Cameron J., Bromhead, Catherine J., Barnett, Christopher B., Royaux, Coline, Gallardo, Cristobal, Blankenberg, Daniel, Fornika, Daniel J., Baker, Dannon, Bouvier, Dave, Clements, Dave, Morais, David A. de Lima, Tabernero, David Lopez, Lariviere, Delphine, Nasr, Engy, Afgan, Enis, Zambelli, Federico, Heyl, Florian, Psomopoulos, Fotis, Coppens, Frederik, Price, Gareth R., Cuccuru, Gianmauro, Le Corguille, Gildas, Von Kuster, Greg, Akbulut, Gulsum Gudukbay, Rasche, Helena, Hans-Rudolf, Hotz, Eguinoa, Ignacio, Makunin, Igor, Ranawaka, Isuru J., Taylor, James P., Joshi, Jayadev, Hillman-Jackson, Jennifer, Goecks, Jeremy, Chilton, John M., Kamali, Kaivan, Suderman, Keith, Poterlowicz, Krzysztof, Yvan, Le Bras, Lopez-Delisle, Lucille, Sargent, Luke, Bassetti, Madeline E., Tangaro, Marco Antonio, van den Beek, Marius, Cech, Martin, Bernt, Matthias, Fahrner, Matthias, Tekman, Mehmet, Foell, Melanie C., Schatz, Michael C., Crusoe, Michael R., Roncoroni, Miguel, Kucher, Natalie, Coraor, Nate, Stoler, Nicholas, Rhodes, Nick, Soranzo, Nicola, Pinter, Niko, Goonasekera, Nuwan A., Moreno, Pablo A., Videm, Pavankumar, Melanie, Petera, Mandreoli, Pietro, Jagtap, Pratik D., Gu, Qiang, Weber, Ralf J. M., Lazarus, Ross, Vorderman, Ruben H. P., Hiltemann, Saskia, Golitsynskiy, Sergey, Garg, Shilpa, Bray, Simon A., Gladman, Simon L., Leo, Simone, Mehta, Subina P., Griffin, Timothy J., Jalili, Vahid, Yves, Vandenbrouck, Wen, Victor, Nagampalli, Vijay K., Bacon, Wendi A., de Koning, Willem, Maier, Wolfgang, and Briggs, Peter J.

Abstract

Galaxy is a mature, browser accessible workbench for scientific computing. It enables scientists to share, analyze and visualize their own data, with minimal technical impediments. A thriving global community continues to use, maintain and contribute to the project, with support from multiple national infrastructure providers that enable freely accessible analysis and training services. The Galaxy Training Network supports free, self-directed, virtual training with >230 integrated tutorials. Project engagement metrics have continued to grow over the last 2 years, including source code contributions, publications, software packages wrapped as tools, registered users and their daily analysis jobs, and new independent specialized servers. Key Galaxy technical developments include an improved user interface for launching large-scale analyses with many files, interactive tools for exploratory data analysis, and a complete suite of machine learning tools. Important scientific developments enabled by Galaxy include Vertebrate Genome Project (VGP) assembly workflows and global SARS-CoV-2 collaborations.

30. Galaxy Training: A powerful framework for teaching!

Author

Hiltemann S, Rasche H, Gladman S, Hotz HR, Larivière D, Blankenberg D, Jagtap PD, Wollmann T, Bretaudeau A, Goué N, Griffin TJ, Royaux C, Le Bras Y, Mehta S, Syme A, Coppens F, Droesbeke B, Soranzo N, Bacon W, Psomopoulos F, Gallardo-Alba C, Davis J, Föll MC, Fahrner M, Doyle MA, Serrano-Solano B, Fouilloux AC, van Heusden P, Maier W, Clements D, Heyl F, Grüning B, and Batut B

Subjects
Humans, Data Analysis, Research Personnel, Software, Computational Biology methods
Abstract

There is an ongoing explosion of scientific datasets being generated, brought on by recent technological advances in many areas of the natural sciences. As a result, the life sciences have become increasingly computational in nature, and bioinformatics has taken on a central role in research studies. However, basic computational skills, data analysis, and stewardship are still rarely taught in life science educational programs, resulting in a skills gap in many of the researchers tasked with analysing these big datasets. In order to address this skills gap and empower researchers to perform their own data analyses, the Galaxy Training Network (GTN) has previously developed the Galaxy Training Platform (https://training.galaxyproject.org), an open access, community-driven framework for the collection of FAIR (Findable, Accessible, Interoperable, Reusable) training materials for data analysis utilizing the user-friendly Galaxy framework as its primary data analysis platform. Since its inception, this training platform has thrived, with the number of tutorials and contributors growing rapidly, and the range of topics extending beyond life sciences to include topics such as climatology, cheminformatics, and machine learning. While initially aimed at supporting researchers directly, the GTN framework has proven to be an invaluable resource for educators as well. We have focused our efforts in recent years on adding increased support for this growing community of instructors. New features have been added to facilitate the use of the materials in a classroom setting, simplifying the contribution flow for new materials, and have added a set of train-the-trainer lessons. Here, we present the latest developments in the GTN project, aimed at facilitating the use of the Galaxy Training materials by educators, and its usage in different learning environments., Competing Interests: We have read the journal’s policy and the authors of this manuscript have the following competing interests: DB has a significant financial interest in GalaxyWorks, a company that may have a commercial interest in the results of this research and technology. This potential conflict of interest has been reviewed and is managed by the Cleveland Clinic. This does not alter our adherence to all the PLOS Computational Biology policies on sharing data and materials., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

Published
2023
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