Galaxy, a web-based genome analysis tool for experimentalists

By Daniel J. Blankenberg, Greg Von Kuster, Nate Coraor, G. Ananda, Ross Lazarus, Mary E. Mangan, Anton Nekrutenko, James Taylor. Current Protocols in Molecular Biology, 2010

1,593 citations recorded by the source corpus.

High‐throughput data production has revolutionized molecular biology. However, massive increases in data generation capacity require analysis approaches that are more sophisticated, and often very computationally intensive. Thus, making sense of high‐throughput data requires informatics support. Galaxy (http://galaxyproject.org) is a software system that provides this support through a framework that gives experimentalists simple interfaces to powerful tools, while automatically managing the computational details. Galaxy is distributed both as a publicly available Web service, which provides tools for the analysis of genomic, comparative genomic, and functional genomic data, or a downloadable package that can be deployed in individual laboratories. Either way, it allows experimentalists without informatics or programming expertise to perform complex large‐scale analysis with just a Web browser. Curr. Protoc. Mol. Biol. 89:19.10.1‐19.10.21. © 2010 by John Wiley & Sons, Inc.

Subfields: Molecular Biology

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Citations in the corpus

SARTools: A DESeq2- and EdgeR-Based R Pipeline for Comprehensive Differential Analysis of RNA-Seq Data (2015, methodology): “Furthermore, the instructions to integrate SARTools into a Galaxy instance [15, 16, 17] are available on the France Bioinformatique Tool Shed1.”
Conducting a Microbiome Study (2014, methodology): “Galaxy (Blankenberg et al., 2010; Giardine et al., 2005; Goecks et al., 2010) and CloVR (Angiuoli et al., 2011) wrappers have been developed to enable access to these tools via the web, and QIIME is also web accessible through the IPython Notebook (Caporaso et al., 2012).”
RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics (2012, background): “Tools like Myrna (14) and Galaxy (15–17) take advantage of cloud and cluster computing to boost performance when processing large data volumes, but rely on an elaborate bioinformatic infrastructure and lack an intuitive user interface.”
Widespread intron retention in mammals functionally tunes transcriptomes (2014, methodology): “The orthology relationships between introns for cross-species comparative IR analyses were obtained by converting the genomic coordinates between genomes using the liftOver tool from Galaxy (Giardine et al. 2005; Blankenberg et al. 2010; Goecks et al. 2010) and selecting 1:1 overlaps.”
Metagenomic biomarker discovery and explanation (2011, methodology): “LEfSe is provided with a graphical interface in the Galaxy framework [46,47], which allows the user to select parameters (the primary three stringency parameters, the multiclass setting, and other computational, statistical, and graphical preferences), to pipeline data between modules in a workflow ”
Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction (2016, methodology): “For these sequences, a phyloP score for each nucleotide (total of 200,000) is calculated using the Galaxy tool [60], [61], [62].”
The genomic landscape of the somatic linker histone subtypes H1.1 to H1.5 in human cells. (2013, methodology): “Normalization and analyses of DamID ell Reports 3, 2142–2154, June 27, 2013 ª2013 The Authors 2151 data were performed using custom R scripts (http://www.r-project.org/), GenPlay software (Lajugie and Bouhassira, 2011), and Galaxy (Blankenberg et al., 2010).”