Usage

October 11, 2019 · View on GitHub

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RNA Galaxy Workbench

The RNA Galaxy workbench is a comprehensive set of analysis tools and consolidated workflows. The workbench is based on the Galaxy framework, which guarantees simple access, easy extension, flexible adaption to personal and security needs, and sophisticated analyses independent of command-line knowledge. The workbench is described in two manuscripts published in Nucleic Acid Research (see version1, version2).

The current implementation comprises more than 50 bioinformatics tools dedicated to different research areas of RNA biology, including RNA structure analysis, RNA alignment, RNA annotation, RNA-protein interaction, ribosome profiling, RNA-Seq analysis, and RNA target prediction.

The workbench is developed by the RNA Bioinformatics Center (RBC). This center is one of the eight service units of the German Network for Bioinformatics Infrastructure, running the German ELIXIR Node.

de.NBI ELIXIR Germany

Usage

The RNA analyses workbench implements a webserver based on the Galaxy Docker platform: a dedicated Galaxy instance wrapped in a Docker container. For advanced local deployments, we recommend to check out the upstream documentation. The workbench is directly use and testable as instance of usegalaxy.eu rna.usegalaxy.eu.

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Requirement

To use the Galaxy RNA workbench, you only need Docker, which can be installed in different ways, depending on the type of system you're running:

  • non-linux users are encouraged to use Kitematic, which provides a Docker installation for OSX or Windows, coupled with a user friendly interface to run Docker containers;
  • linux users and people familiar with the command line can follow the instruction on installing Docker from its website.

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Docker configuration

The RNA workbench docker container is rather large and expected to grow when further tools and workflows are contributed. So for users new to docker, we list here some tweaks that can help to work around issues when first using docker. After successful installation of docker, it is recommended to configure some settings, dealing for example with the storage space required by containers. You can find more information here.

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RNA workbench launch

Whether you run Docker images using Kitematic or the command line interface, the procedure to launch the RNA workbench varies.

Using Kitematic

Kitematic users can launch the RNA workbench directly from its interface. The following video shows how to load the docker container that is necessary to use the workbench:

Kitematic galaxy-rna-workbench launch

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Without Kitematic

For non-Kitematic users, starting the RNA workbench is analogous to start the generic Galaxy Docker image:

$ docker run -d -p 8080:80 quay.io/bgruening/galaxy-rna-workbench

A detailed discussion of Docker's parameters is given in the Docker manual. It is really worth reading. Nevertheless, here is a quick rundown:

  • docker run starts the Image/Container

    In case the Container is not already stored locally, docker downloads it automatically

  • The argument -p 8080:80 makes the port 80 (inside of the container) available on port 8080 on your host

    Inside the container a Apache web server is running on port 80 and that port can be bound to a local port on your host computer. With this parameter you can access your Galaxy instance via http://localhost:8080 immediately after executing the command above

  • quay.io/bgruening/galaxy-rna-workbench is the Image/Container name, that directs docker to the correct path in the docker index

  • -d will start the docker container in Daemon mode.

    For an interactive session, one executes:

    $ docker run -i -t -p 8080:80 quay.io/bgruening/galaxy-rna-workbench /bin/bash
    

    and manually invokes the startup script to start PostgreSQL, Apache and Galaxy.

Docker images are "read-only". All changes during one session are lost after restart. This mode is useful to present Galaxy to your colleagues or to run workshops with it.

To install Tool Shed repositories or to save your data, you need to export the calculated data to the host computer. Fortunately, this is as easy as:

$ docker run -d -p 8080:80 -v /home/user/galaxy_storage/:/export/ quay.io/bgruening/galaxy-rna-workbench

Given the additional -v /home/user/galaxy_storage/:/export/ parameter, docker will mount the folder /home/user/galaxy_storage into the Container under /export/. A startup.sh script, that is usually starting Apache, PostgreSQL and Galaxy, will recognize the export directory with one of the following outcomes:

  • In case of an empty /export/ directory, it will move the PostgreSQL database, the Galaxy database directory, Shed Tools and Tool Dependencies and various configure scripts to /export/ and symlink back to the original location.
  • In case of a non-empty /export/, for example if you continue a previous session within the same folder, nothing will be moved, but the symlinks will be created.

This enables you to have different export folders for different sessions - meaning real separation of your different projects.

It will start the Galaxy RNA workbench with the configuration and launch of a Galaxy instance and its population with the needed tools. The instance will be accessible at http://localhost:8080.

For a more specific configuration, you can have a look at the documentation of the Galaxy Docker Image.

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Users and passwords

The Galaxy Admin User has the username admin@galaxy.org and the password admin. In order to use certain features of Galaxy, like e.g. the RNA structure visualization, one has to be logged in. Also the installation of additional tools requires a login.

The PostgreSQL username is galaxy, the password galaxy and the database name galaxy.

If you want to create new users, please make sure to use the /export/ volume. Otherwise your user will be removed after your docker session is finished.

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Tours

The RNA workbench provides the possibility to run interactive tours that illustrate how the main interface works in relation to real-life user tasks. These show many common operations, such as searching, parametrizing, and running tools, or saving a history of operations in a sharable workflow.

The following video demonstrates the main elements that compose the Galaxy user interface:

Galaxy UI tour

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Available tools

In this section we list all tools that have been integrated in the RNA workbench. The list is likely to grow as soon as further tools and workflows are contributed. To ease readability, we divided them into categories.

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RNA structure prediction and analysis

ToolDescriptionReference
antaRNAPossibility of inverse RNA structure folding and a specification of a GC value constraintKleinkauf et al. 2015
CoFoldA thermodynamics-based RNA secondary structure folding algorithmProctor et al. 2013
CMCompareTool to compare RNA families via covariance modelsEggenhofer et al. 2013
KinwalkerAlgorithm for cotranscriptional folding of RNAs to obtain the min. free energy structureGeis et al. 2008
MEAPrediction of maximum expected accuracy RNA secondary structuresAmman et al. 2013
RNAlienA tool for RNA family model constructionEggenhofer et al. 2016
RNAshapesStructures to a tree-like domain of shapes, retaining adjacency and nesting of structural featuresJanssen et al. 2014
RNAzPredicts structurally conserved and therm. stable RNA secondary structures in mult. seq. alignmentsGruber et al. 2010
segmentation-foldAn application that predicts RNA 2D-structure with an extended version of the Zuker algorithm
ViennaRNAA tool compilation for prediction and comparison of RNA secondary structuresLorenz et al. 2011

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RNA alignment

ToolDescriptionReference
CMVRNA family model visualisationEggenhofer et al. 2018
CompalignpAn RNA counterpart of the protein specific "Benchmark Alignment Database"Wilm et al. 2006
LocARNAA tool for multiple alignment of RNA moleculesWill et al. 2012
MAFFTA multiple sequence alignment program for unix-like operating systemsKatoh and Standley 2016
RNAlienA tool for RNA family model constructionEggenhofer et al. 2016

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RNA annotation

ToolDescriptionReference
ARAGORNA tool to identify tRNA and tmRNA genesLaslett et al. 2004
FuMa (Fusion Matcher)A tool to reports identical fusion genes based on gene-name annotationsHoogstrate et al. 2015
GotohScanA search tool to find shorter sequences in large database sequencesHertel et al. 2009
InfernalSuite of tools for building RNA families covariance models (CMs) from structurally annotated sequence alignmentsNawrocki et al. 2013
RNABOBA tool for fast pattern matching of RNA secondary structuresGautheret et al. 1990
RNAcodePredicts protein coding regions in a set of homologous nucleotide sequencesWashietl et al. 2011
tRNAscanSearches for tRNA genes in genomic sequencesLowe et al. 1997
RCASA generic reporting tool for the functional analysis of transcriptome-wide regions of interest detected by high-throughput experimentsUyar et al. 2017

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RNA-protein interaction

ToolDescriptionReference
AREsite2A database for AU-/GU-/U-rich elements in human and model organismsFallmann et al. 2015
doRiNAA database of RNA interactions in post-transcriptional regulationBlin et al. 2014
PARalyzerAn algorithm to generate a map of interacting RNA-binding proteins and their targetsCorcoran et al. 2011
PiranhaA peak-caller for CLIP- and RIP-seq data

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RNA-RNA interaction

ToolDescriptionReference
IntaRNAEfficient RNA-RNA interaction prediction incorporating accessibility and seeding of interaction sitesMann et al. 2017

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RNA target prediction

ToolDescriptionReference
TargetFinderA tool to predict small RNA binding sites on target transcripts from a sequence databaseFahlgren et al. 2009

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Ribosome profiling

ToolDescriptionReference
RiboTaperAn analysis pipeline for Ribo-Seq experiments, exploiting the triplet periodicity of ribosomal footprints to call translated regionsCalviello et al. 2015

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RNA-Seq and HTS analysis

Quality control

ToolDescriptionReference
FastQC!A quality control tool for high throughput sequence data
mQCA quality control tool for ribosome profiling mapping resultsVerbruggen and Menschaert 2017
MultiQCA tool to create reports visualising output from multiple tools across many samplesEwels et al. 2016
Trim Galore!A tool for the automation of quality and adapter trimming on paired-end or non-paired-end end sequences

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RNA-Seq

ToolDescriptionReference
Dr. DiscoAn analysis pipeline to detect genomic breakpoints in RNA-Seq data
FlaiMapperA tool for computational annotation of small ncRNA-derived fragments using RNA-seq dataHoogstrate et al. 2014
NASTIseqA method that incorporates the inherent variable efficiency of generating perfectly strand-specific librariesLi et al. 2013
PIPmiRAn algorithm to identify novel plant miRNA genes from a combination of deep sequencing data and genomic featuresBreakfield et al. 2011
SortMeRNAA tool for filtering, mapping and OTU-picking NGS reads in metatranscriptomic and -genomic dataKopylova et al. 2011

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Read mapping

ToolDescriptionReference
Bowtie2Fast and sensitive read alignmentLangmead et al. 2012
BWABurrows-Wheeler Aligner for mapping low-divergent sequences against a large reference genomeLi and Durbin 2010
BWA-MEMFast and accurate long-read alignment with Burrows-Wheeler transformLi et al. 2010
HISAT2Hierarchical indexing for spliced alignment of transcriptsKim et al. 2015
RNA STARRapid spliced aligner for RNA-seq dataDobin et al. 2013
STAR-fusionFast fusion gene finderHaas et al. 2017

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Transcript assembly

ToolDescriptionReference
TrinityDe novo transcript sequence reconstruction from RNA-SeqHaas et al. 2013

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Transcript quantification

ToolDescriptionReference
featureCountsUltrafast and accurate read summarization programLiao et al. 2014
SailfishRapid alignment-free quantification of isoform abundancePatro et al. 2014
SalmonFast, accurate and bias-aware transcript quantificationPatro et al. 2017

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Differential expression analysis

ToolDescriptionReference
DESeq2Differential gene expression analysis based on the negative binomial distributionLove et al. 2014

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Utilities

ToolDescriptionReference
SAMtoolsUtilities for manipulating alignments in the SAM formatHeng et al. 2009
BEDToolsUtilities for genome arithmeticQuinlan et al. 2010
deepToolsA suite of tools for exploring hight-throughput sequencing data (HTS), such as ChIP-seq, RNA-seq, and MNase-seqRamirez et al. 2016

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Training

To learn about RNA sequencing data analysis, we recommend you to have a look at the training material from the Galaxy Training network, particularly the tutorial on Reference-based RNA-seq data analysis.

In the Galaxy RNA workbench, we also included Galaxy interactive tours to guide you through the Galaxy, it's tools and possibilities.

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Contributors

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How to contribute

The RNA-workbench community welcomes new contributions and help in any way. We have collected detailed instructions and some guidance in our CONTRIBUTING.md.

Support and bug reports

For support, questions, or feature requests fill bug reports on our issue page.

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MIT license

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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