Galaxy: A Web‐Based Genome Analysis Tool for Experimentalists

Blankenberg, Daniel; Kuster, Gregory Von; Coraor, Nathaniel; Ananda, Guruprasad; Lazarus, Ross; Mangan, Mary; Nekrutenko, Anton; Taylor, James

doi:10.1002/0471142727.mb1910s89

Cited by 1,195 publications

(935 citation statements)

References 4 publications

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“…These examples were chosen to showcase edgeR’s ability to deal with experiments of varying size (from tens to thousands of hairpins) and complexity, from two-group situations, to settings with four groups, or a time-course design, where a GLM with a slope and intercept term is most appropriate. We have also developed a Galaxy tool 15– 17 that implements this workflow as a point-and-click application to improve accessibility for researchers who are unfamiliar with the R programming environment ( Figure 2). …”

Section: Methodsmentioning

confidence: 99%

shRNA-seq data analysis with edgeR

et al. 2014

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Pooled short hairpin RNA sequencing (shRNA-seq) screens are becoming increasingly popular in functional genomics research, and there is a need to establish optimal analysis tools to handle such data. Our open-source shRNA processing pipeline in edgeR provides a complete analysis solution for shRNA-seq screen data, that begins with the raw sequence reads and ends with a ranked lists of candidate shRNAs for downstream biological validation. We first summarize the raw data contained in a fastq file into a matrix of counts (samples in the columns, hairpins in the rows) with options for allowing mismatches and small shifts in hairpin position. Diagnostic plots, normalization and differential representation analysis can then be performed using established methods to prioritize results in a statistically rigorous way, with the choice of either the classic exact testing methodology or a generalized linear modelling that can handle complex experimental designs. A detailed users’ guide that demonstrates how to analyze screen data in edgeR along with a point-and-click implementation of this workflow in Galaxy are also provided. The edgeR package is freely available from http://www.bioconductor.org.

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Section: Methodsmentioning

confidence: 99%

shRNA-seq data analysis with edgeR

et al. 2014

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“…Richness estimators, diversity indices and coverage percentage were calculated from randomly subsampled set of sequences (based on the smallest dataset) in mothur. To visualize the number and correlation of taxa at different taxonomic ranks among samples, CoVennTree (Lott et al, 2015) was used, a tool on the Galaxy platform (Giardine et al, 2005;Blankenberg et al, 2010;Goecks et al, 2010). The resulted output was visualized in Cytoscape 2.8.3 (Shannon et al, 2003).…”

Section: 4pyrosequencingmentioning

confidence: 99%

Gut content microbiota of introduced bigheaded carps ( Hypophthalmichthys spp.) inhabiting the largest shallow lake in Central Europe

Borsodi

Krett

Felföldi

et al. 2017

Microbiological Research

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Studying the microbiota in the alimentary tract of bigheaded carps (Hypophthalmichthys spp.) gained special interest recently, as these types of investigations on non-native fish species may lead to a better understanding of their ecological role and feeding habits in an invaded habitat. For microbiological examinations, bigheaded carp gut contents and water column samples from Lake Balaton (Hungary) were collected from spring to autumn in 2013.Denaturing Gradient Gel Electrophoresis (DGGE) and pyrosequencing of the 16S rRNA gene were performed to reveal the composition. According to the DGGE patterns, bacterial communities of water samples separated clearly from that of the intestines. Moreover, the bacterial communities in the foreguts and hindguts were also strikingly dissimilar. Based on pyrosequencing, both foregut and hindgut samples were predominated by the fermentative genus Cetobacterium (Fusobacteria). The presence of some phytoplankton taxa and the high relative abundance of cellulose-degrading bacteria in the guts suggest that intestinal microbes may have an important role in digesting algae and making them utilizable for bigheaded carps that lack cellulase enzyme. In turn, the complete absence of typical heterotrophic freshwater bacteria in all studied sections of the intestines indicated that bacterioplankton probably has a negligible role in the nutrition of bigheaded carps.

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“…It is developed on the Galaxy platform and composed of a combination of Python and R components together, creating a straightforward data flow (22,23). ARGalaxy consists of four parts: one tool for demultiplexing and sequence trimming of .sff files (the demultiplex tool); one tool that allows concatenating IMGT/High V-QUEST files (the IMGT concatenate tool); the immune repertoire pipeline, which allows for the study of V(D)J gene usage, CDR3 and junction characteristics, and the diversity of all immune receptor genes; and finally the SHM and CSR pipeline for the analysis of SHM and Ag selection in IGH, IGK, and IGL rearrangements, and CSR in the IGH rearrangements.…”

Section: Resultsmentioning

confidence: 99%

Antigen Receptor Galaxy: A User-Friendly, Web-Based Tool for Analysis and Visualization of T and B Cell Receptor Repertoire Data

IJspeert

Schouwenburg

Zessen

et al. 2017

The Journal of Immunology

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Antigen Receptor Galaxy (ARGalaxy) is a Web-based tool for analyses and visualization of TCR and BCR sequencing data of 13 species. ARGalaxy consists of four parts: the demultiplex tool, the international ImMunoGeneTics information system (IMGT) concatenate tool, the immune repertoire pipeline, and the somatic hypermutation (SHM) and class switch recombination (CSR) pipeline. Together they allow the analysis of all different aspects of the immune repertoire. All pipelines can be run independently or combined, depending on the available data and the question of interest. The demultiplex tool allows data trimming and demultiplexing, whereas with the concatenate tool multiple IMGT/HighV-QUEST output files can be merged into a single file. The immune repertoire pipeline is an extended version of our previously published ImmunoGlobulin Galaxy (IGGalaxy) virtual machine that was developed to visualize V(D)J gene usage. It allows analysis of both BCR and TCR rearrangements, visualizes CDR3 characteristics (length and amino acid usage) and junction characteristics, and calculates the diversity of the immune repertoire. Finally, ARGalaxy includes the newly developed SHM and CSR pipeline to analyze SHM and/or CSR in BCR rearrangements. It analyzes the frequency and patterns of SHM, Ag selection (including BASELINe), clonality (Change-O), and CSR. The functionality of the ARGalaxy tool is illustrated in several clinical examples of patients with primary immunodeficiencies. In conclusion, ARGalaxy is a novel tool for the analysis of the complete immune repertoire, which is applicable to many patient groups with disturbances in the immune repertoire such as autoimmune diseases, allergy, and leukemia, but it can also be used to address basic research questions in repertoire formation and selection.

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Galaxy: A Web‐Based Genome Analysis Tool for Experimentalists

Cited by 1,195 publications

References 4 publications

shRNA-seq data analysis with edgeR

shRNA-seq data analysis with edgeR

Gut content microbiota of introduced bigheaded carps ( Hypophthalmichthys spp.) inhabiting the largest shallow lake in Central Europe

Antigen Receptor Galaxy: A User-Friendly, Web-Based Tool for Analysis and Visualization of T and B Cell Receptor Repertoire Data

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