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Laniakea@ReCaS: exploring the potential of customisable Galaxy on-demand instances as a cloud-based service

Marco Antonio Tangaro, Pietro Mandreoli, Matteo Chiara, Giacinto Donvito, Marica Antonacci, Antonio Parisi, Angelica Bianco, Angelo Romano, Daniela Manila Bianchi, Davide Cangelosi, Paolo Uva, Ivan Molineris (+9 others)
2021 BMC Bioinformatics  
By facilitating the set-up and configuration of Galaxy web servers, Laniakea provides researchers with a powerful and highly customisable platform for executing complex bioinformatics analyses.  ...  The system can be accessed through a dedicated and user-friendly web interface that allows the Galaxy web server's initial configuration and deployment.  ...  We are grateful to BIOGEN biobank-a member of the Telethon Network of Genetic Biobanks (Project No. GTB12001), funded by Telethon Italywhich provided the biological samples for Use Case 8.  ... 
doi:10.1186/s12859-021-04401-3 pmid:34749633 pmcid:PMC8574934 fatcat:jszcn3pt4zdxxddlhw7qm5d3su

Reproducible Data Analysis Pipelines for Precision Medicine [article]

Bjørn Fjukstad, Vanessa Dumeaux, Michael Hallett, Lars Bongo
2018 bioRxiv   pre-print
Technologies such as high-throughput sequencing enable cheaper data collection at higher speed, but rely on modern data analysis platforms to extract knowledge from these high dimensional datasets.  ...  Precision medicine brings the promise of more precise diagnosis and individual-zed therapeutic strategies from analyzing a cancer's genomic signature.  ...  Acknowledgements We would like to thank Daniel Del Balso for his work implementing the initial WGS analysis pipeline.  ... 
doi:10.1101/354811 fatcat:tvg7stc3lvd4fczdi77gveue24

Experiences building Globus Genomics: a next-generation sequencing analysis service using Galaxy, Globus, and Amazon Web Services

Ravi K. Madduri, Dinanath Sulakhe, Lukasz Lacinski, Bo Liu, Alex Rodriguez, Kyle Chard, Utpal J. Dave, Ian T. Foster
2014 Concurrency and Computation  
We describe Globus Genomics, a system that we have developed for rapid analysis of large quantities of next-generation sequencing (NGS) genomic data.  ...  This system achieves a high degree of end-to-end automation that encompasses every stage of data analysis including initial data retrieval from remote sequencing centers or storage (via the Globus file  ...  ., for an award of Amazon Web Services time that facilitated early experiments. We thank Globus Genomics users for their invaluable contributions.  ... 
doi:10.1002/cpe.3274 pmid:25342933 pmcid:PMC4203657 fatcat:glcie6spdzdllakjibkyniqo5y

High-Performance Integrated Virtual Environment (HIVE) Tools and Applications for Big Data Analysis

Vahan Simonyan, Raja Mazumder
2014 Genes  
The High-performance Integrated Virtual Environment (HIVE) is a high-throughput cloud-based infrastructure developed for the storage and analysis of genomic and associated biological data.  ...  HIVE consists of a web-accessible interface for authorized users to deposit, retrieve, share, annotate, compute and visualize Next-generation Sequencing (NGS) data in a scalable and highly efficient fashion  ...  Acknowledgements We would like to acknowledge the following people for providing feedback and HIVE support:  ... 
doi:10.3390/genes5040957 pmid:25271953 pmcid:PMC4276921 fatcat:fpkwi7qj6bhkxp6y3k2nxv2lre

Cloud Computing for Next-Generation Sequencing Data Analysis [chapter]

Shanrong Zhao, Kirk Watrous, Chi Zhang, Baohong Zhang
2017 Cloud Computing - Architecture and Applications  
share the lessons we learned from the implementation of Rainbow, a cloud-based tool for large-scale genome sequencing data analysis.  ...  High-throughput next-generation sequencing (NGS) technologies have evolved rapidly and are reshaping the scope of genomics research.  ...  Galaxy Cloud [57] , a cloudbased Galaxy platform for the analysis of data at a large scale, is the most used platform for bioinformatics.  ... 
doi:10.5772/66732 fatcat:2ewdbtp2bjhx7j7tj4e3auwqke

The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR

Daniel Wibberg, Bérénice Batut, Peter Belmann, Jochen Blom, Frank Oliver Glöckner, Björn Grüning, Nils Hoffmann, Nils Kleinbölting, René Rahn, Maja Rey, Uwe Scholz, Malvika Sharan (+4 others)
2019 F1000Research  
The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers.  ...  The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF).  ...  For post-genomic analyses, there is a workshop on the analysis, visualization and integration of multi-level -omics data, which introduces the web-based platform Omics-Fusion 17 .  ... 
doi:10.12688/f1000research.20244.1 pmid:33163154 pmcid:PMC7607484 fatcat:g4gztfjahrbkdepxw6rgkjfhjy

Selected Approaches and Frameworks to Carry out Genomic Data Analysis on the Cloud

Philip Church, Andrzej Goscinski
2015 Scalable Computing : Practice and Experience  
While High Performance Computing clouds allow researchers to process large amounts of genomic data, complex resource and software configuration tasks must be carried out beforehand.  ...  This paper examines commonly used cloud-based genomic analysis services, introduces the approach of exposing data as services and proposes two new solutions (HPCaaS and Uncinus) which aim to automate service  ...  obtained from a IaaS cloud, and (iii) the Galaxy software application used as a web-based platform for exposing and accessing HPC application services.  ... 
doi:10.12694/scpe.v16i1.1058 fatcat:7snkmbj24ra27m5mhpgrbs4mzq

Will digital pathology be as disruptive as genomics?

StevenN Hart
2018 Journal of Pathology Informatics  
Acknowledgments The author would like to thank the Mayo Clinic Center for Individualized Medicine and Department of Laboratory Medicine and Pathology for funding this work.  ...  Lessons Learned from GenomIcs that Inform dIGItaL PathoLoGy Growth There are at least five significant "lessons learned" during the growth of genomics that are well suited to be transferred to digital  ...  Many of the lessons learned from genomics can, therefore, be applied. the cost of data The significant expense can be invested to generate digital data from genomics and digital pathology.  ... 
doi:10.4103/jpi.jpi_25_18 pmid:30167342 pmcid:PMC6106127 fatcat:n2jzal2vvvdapbcpzlz6c4t3jm

Experiences with workflows for automating data-intensive bioinformatics

Ola Spjuth, Erik Bongcam-Rudloff, Guillermo Carrasco Hernández, Lukas Forer, Mario Giovacchini, Roman Valls Guimera, Aleksi Kallio, Eija Korpelainen, Maciej M Kańduła, Milko Krachunov, David P Kreil, Ognyan Kulev (+6 others)
2015 Biology Direct  
High-throughput technologies, such as next-generation sequencing, have turned molecular biology into a data-intensive discipline, requiring bioinformaticians to use high-performance computing resources  ...  Based on our experiences we define a set of recommendations for future systems to enable efficient yet simple bioinformatics workflow construction and execution.  ...  MK and OK were supported by National Science Fund of Bulgaria within the "Methods for Data Analysis and Knowledge Discovery in Big Sequencing Dataset" project under contract DFNI02/7 of 12.12.2014.  ... 
doi:10.1186/s13062-015-0071-8 pmid:26282399 pmcid:PMC4539931 fatcat:cxotvdjwrndblm7gvu5myegsrq

Bioexcel Deliverable 2.1 – State Of The Art And Gap Analysis

Adam Hospital, Anna Montras, Stian Soiland-Reyes, Alexandre Bonvin, Adrien Melquiond, Josep Lluís Gelpí, Daniele Lezzi, Steven Newhouse, Jose A. Dianes, Mark Abraham, Rossen Apostolov, Emiliano Ippoliti (+2 others)
2016 Zenodo  
Based o [...]  ...  Finally, we realized that a high number of users would be interested in using remote tools, although several concerns have been raised about this, namely data privacy, reliability, and lack of control.  ...  Galaxy Galaxy is an open, web-based platform for data intensive biomedical research. Galaxy can be accessed on a free public server http://usegalaxy.org/, or installed locally in the lab.  ... 
doi:10.5281/zenodo.263963 fatcat:o2v7ogjmnbauhn7txp2buz3pem

The de.NBI / ELIXIR-DE training platform - Bioinformatics training in Germany and across Europe within ELIXIR

Daniel Wibberg, Bérénice Batut, Peter Belmann, Jochen Blom, Frank Oliver Glöckner, Björn Grüning, Nils Hoffmann, Nils Kleinbölting, René Rahn, Maja Rey, Uwe Scholz, Malvika Sharan (+4 others)
2020 F1000Research  
The network provides a high-quality, coherent, timely, and impactful training program across its eight service centers.  ...  The German Network for Bioinformatics Infrastructure (de.NBI) is a national and academic infrastructure funded by the German Federal Ministry of Education and Research (BMBF).  ...  For post-genomic analyses, there is a workshop on the analysis, visualization and integration of multi-level -omics data, which introduces the web-based platform Omics-Fusion 20 .  ... 
doi:10.12688/f1000research.20244.2 fatcat:io4rgsengvddhlhwjgpqv5livu

Reproducible biomedical benchmarking in the cloud: lessons from crowd-sourced data challenges

Kyle Ellrott, Alex Buchanan, Allison Creason, Michael Mason, Thomas Schaffter, Bruce Hoff, James Eddy, John M. Chilton, Thomas Yu, Joshua M. Stuart, Julio Saez-Rodriguez, Gustavo Stolovitzky (+2 others)
2019 Genome Biology  
We review recent data challenges with innovative approaches to model reproducibility and data sharing, and outline key lessons for improving quantitative biomedical data analysis through crowd-sourced  ...  Challenges are achieving broad acceptance for addressing many biomedical questions and enabling tool assessment.  ...  Solutions that involve a single lab distributing a package of tools and documentation for running on a single dataset or running a low throughput web server will not scale.  ... 
doi:10.1186/s13059-019-1794-0 pmid:31506093 pmcid:PMC6737594 fatcat:njzmseerufcghihkoiskuqq6km

Reproducible biomedical benchmarking in the cloud: lessons from crowd-sourced data challenges

Kyle Ellrott, Alex Buchanan, Allison Creason, Michael Mason, Thomas Schaffter, Bruce Hoff, James Eddy, John M. Chilton, Thomas Yu, Joshua M. Stuart, Julio Saez-Rodriguez, Gustavo Stolovitzky (+2 others)
2019 Genome Biology  
We review recent data challenges with innovative approaches to model reproducibility and data sharing, and outline key lessons for improving quantitative biomedical data analysis through crowdsourced benchmarking  ...  Challenges are achieving broad acceptance for addressing many biomedical questions and enabling tool assessment.  ...  Solutions that involve a single lab distributing a package of tools and documentation for running on a single dataset or running a low throughput web server will not scale.  ... 
doi:10.18154/rwth-conv-241869 fatcat:hjaabhhqvfel7denahvnxab75i

Deliverable JIP1-2.8 - Status report on OH Knowledge Base - NGS

Karin Lagesen, Umaer Naseer, Emily Macdonald, Lin Brandal, Olaug Taran Skjerdal, Thomas H.A. Haverkamp, Eve Zeyl Fiskebeck, Jeevan Karloss Antony Samy, Georgios Marselis, Camilla Sekse, Håkon Kaspersen, Wonhee Cha (+8 others)
2021 Zenodo  
The web platform uses Galaxy as its workflow engine, and thus uses Galaxy for managing pipelines and sequencing tools.  ...  These were the INNUENDO and the IRIDA systems, which seemed to be functional, active, up-to-date platforms which could manage and analyze high throughput microbial genomics data combined with visualization  ...  A continuous analysis and comparison of the human-food isolates were done and the genome sequences from food/animas were send to SSI for analysis.  ... 
doi:10.5281/zenodo.5062329 fatcat:mca5ix3ojzewzd5gyyq7g6gm5a

Incorporating computational resources in a cancer research program

Nicholas T. Woods, Ankita Jhuraney, Alvaro N. A. Monteiro
2014 Human Genetics  
Here, we discuss the lessons learned in our laboratory and share several recommendations to make this transition effectively.  ...  However, a significant effort is required to adapt a molecular biology-based research program to take advantage of these datasets.  ...  Acknowledgments Work in the Monteiro Lab is funded by NIH awards U19 CA148112 (GAME-ON consortium), U01 CA116167, R21 CA184996 (to N.W.) and by awards from the Moffitt Foundation.  ... 
doi:10.1007/s00439-014-1496-3 pmid:25324189 pmcid:PMC4401625 fatcat:gkrgo3kbsnag3hadp67q3pzqcq
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