Grape is a pipeline for processing and analyzing RNA-Seq data
High throughput sequencing technologies generate vast amounts of data that require subsequent management, analysis and visualization.
The Grape RNAseq Analysis Pipeline Environment implements a set of workflows that allow for easy exploration of RNA-Seq data. Among other features, it enables the users to perform
- quality checks
- read mapping
- generation of expression and splicing statistics
The results are stored in a MySQL database and become immediately available through a RESTful back end server that is connected to a web application using the Google chart tools for display.
The documentation is hosted here: http://grapebuildout.readthedocs.org
Download the latest stable versions of Grape from here:
Follow the instructions in the README.txt
Knowles D, Röder M, Merkel A, Guigó R.
Bioinformatics. 2013 Mar 1;29(5):614-21. doi: 10.1093/bioinformatics/btt016. Epub 2013 Jan 17.
Check out the development version of Grape:
Then follow the steps in the README.txt
You need to have access to a
- MySQL database
Make sure to have the following standard programming languages installed:
The following Perl modules must be installed
You need to have the following module installed in Python:
To give you a preview of the statistical results produced by Grape, our lab has published a set of results for the following RNASeq projects:
New in Grape 1.9.5 (2013-10-21):
- update bootstrap.py from http://downloads.buildout.org/1/bootstrap.py
- Upgrade to grape.recipe.pipeline 1.1.16
- Better error message when the type parameter in the accession is neither fastq nor bam
New in Grape 1.9.4 (2013-02-13):
- Make TEMPLATE parameter optional, the right one is chosen by default now
- Detect wrong template for fastq and bam files.
New in Grape 1.9.3 (2013-02-12):
- Fix configuration checks for bam files
- Allow plus sign in parameter values
- Use a single bootstrap.py, and update the documentation
New in Grape 1.9.2 (2013-01-09):
- New MAXINTRONLENGTH option: Sets the maximum length of splits allowed during the postprocessing of the files generated by gem-2-sam removing the noise. The default is set to 50000, which is reasonable in mammals, however different species may require different settings. Setting it to 0 will remove this filter.
- Improve the documentation for grape.recipe.pipeline: https://graperecipepipeline.readthedocs.org/en/latest/
New in Grape 1.9.1 (2012-12-09):
- Fix bug that caused an uninitialized value in exon, junction and transcript tables when the initial fasta_file table was not present in the database.
New in Grape 1.9 (2012-11-11):
- The charts shown in the Raisin web application now have a better layout and a proper title.
- Fix Quick runs. Soft links were not made correctly, and some accession parameters are now filled in correctly as well.
- add FLUXMEM parameter to control the maximum number of GB of memory that the Flux can use
- add MIN_RECURSIVE_MAPPING_TRIM_LENGTH parameter that allows tuning the minimum length to which a read will be trimmed during the recursive mapping.
- check read labels for consistency
- Add the basic scripts to run the IDR. This is not incorporated yet to the pipeline itself, but the scripts can be used to run it.
- Servers now have a project_downloads and project_downloads_folder section that can be configured in servers/devel/buildout.cfg
New in Grape 1.8 (2012-10-09):
- Use new Cufflinks, version 2.0.2
- Upgrade to Grape pipeline 6.5
- Allow for the running of the start script with only species, genome, annotation and read length specified appart from a list of one or two files.
- Set the number of CPUs used by fastqc to one.
- new dependency on grape.recipe.pipeline to share validation code with the Raisin
- Fix a bug that prevented the correct running of the Flux when the read Ids came from HiSeq
- Add verbose to the mysqlimport statement in the build_exon_junctions.RNAseq.pl
- Install the pre version of GEM in grape.recipe.pipeline 1.1.9, with binaries prefixed with "next".
- Download packages from PyPI instead of from the SVN
- add .downloads and .eggs folders
- Raisin web server
- The download paths and the project folders are now configured in the buildout.cfg
- Remove pickle caching code
- Remove code previously used for dumping resources
- Move dumps folder to the top
- improve .gitignore
- pin MySQL-python = 1.2.3
New in Grape 1.7 (2012-07-25):
- Fix a bug that prevented the pipeline from building the inclusion exclusion table
- Speed up the recursive mapping part of the pipeline
- The output from the Flux capacitor is not deleted any more, making it available for further analysis
- In the Raisin web application, links are now shorter when pointing to pages with tabs. For example, it is not necessary to add /tab/experiments to URLs any more, if the experiments tab is the default tab.
New in Grape 1.6 (2012-07-10):
- Now creates the var/log folder needed when starting raisin with supervisord
- Raisin can now be installed even if some annotation information is missing
- Now correctly gets all the scores in qualities and ambiguous
- Parsing reads is fixed
- HiSEq read IDs are now handled
New in Grape 1.5 (2012-07-06):
- Installs and integrates FastQC
- Default parameters to make configuration easier. When no project parameters are given, use read_length. When no project user is given, use anonymous
New in Grape 1.4 (2012-06-27):
Install Cufflinks 2.0.1 binaries and use it for detecting novel transcripts
Use FastQC for quality control
Calculate gene and exon RPKM now from the Flux Capacitor results
New in Grape 1.3 (2012-05-18):
Integrating version 6.0 of the pipeline that now depends on a new version of the Flux-Capacitor: 1.0 RC2.
Speed improvements: The pipeline now relies less on the overlap tool by using information already included in the BAM files.
New in Grape 1.2 (2012-04-20):
The automatic installation of dependencies has changed. Before, they were taken from the SVN using mr.developer. Now that releases are available for the packages needed by the pipeline, they are downloaded from our web server using the hexagonit.recipe.download recipe, or taken from PyPI (See grape.recipe.pipeline) using zc.recipe.egg.
New in Grape 1.1.2 (2012-03-30):
Moved the installation instructions to INSTALL.txt and added a README.txt to pipelines/Quick.
New in Grape 1.1.1 (2012-03-30):
Grape 1.1.1 includes a better README.txt that will guide you throught the installation process.
New in Grape 1.1 (2012-03-29):
Grape 1.1 allows you to quickly analyse one set of RNAseq reads without a lot of configuration overhead.
We provide annotations and genomes that are known to work perfectly for the following species:
- Homo sapiens
- Caenorhabditis elegans (Coming soon)
- Mus musculus
- Drosophila Melanogaster
All versions of Grape: