We are very excited to announce that the
expert-preferred suite of RNA-Seq data analysis software is now available on BaseSpace for a ny researcher, irrespective of bioinformatics experience. The BaseSpace Core Apps for RNA are based on the Tuxedo suite of RNA analysis tools:
● The TopHat Alignment App can be used to align RNA reads as well as detect gene fusions using the industry-standard method. Illumina’s Isaac method further enables the calling of SNVs and small indels.
● Cufflinks enables gene expression profiling and detection of novel transcript isoforms.
These applications are packaged in an intuitive, click-and-go user interface that is designed to enable any bench biologist to process their own data, from start to finish. The pipeline generates easily-interpretable, publication-ready data in clear tables and graphs, and also provides output files that can be submitted as input into any number of third-party secondary analysis tools. As a result, BaseSpace Core Apps for RNA can be applied to a broad range of research projects, including:
- Gene expression profiling
- mRNA expression profiling, including transcript-level abundance, and discovery of novel features including alternate transcripts
- Total RNA expression profiling, including detection of gene fusions and cSNPs
Importantly, RNA-Seq apps work with data from all Illumina instruments, NextSeq, HiSeq, and MiSeq – and are
compatible with the complete portfolio of TruSeq RNA sample preparation solutions. This includes the newly announced TruSeq RNA Access Kit – a highly robust, low sequencing output-requiring solution for FFPE samples.
And because the BaseSpace Core Apps for RNA leverage the inherent parallelism of the cloud, the time-to-answer can be as little as four minutes per sample for gene-expression profiling experiments.
The RNA-Seq apps are uniquely suited to perform comprehensive cancer research studies. As the TCGA and other consortia have repeatedly shown, adding RNA-Seq analysis to a DNA sequencing project is critical for identifying the biological significance of somatic mutations in cancer. Without the RNA-Seq results, it is difficult to assess whether the gene(s) harboring the somatic mutations are expressed at all in the cancer sample. Moreover, the patterns of expression among related genes, and the detection of gene fusions, so critical to cancer research, can only be elucidated with an RNA-Seq experiment. Finally, robust sample preparation solutions for FFPE-stored cancer samples are now unlocked so that researchers can carry out comprehensive, multi-assay studies to advance their research.
The RNA-Seq apps have been designed with an obsessive focus on accessibility. The traditional command-line versions of these apps require expert bioinformaticians to maintain and run the tools, in-house IT staff to maintain the hardware, and a fairly massive compute infrastructure. But with the RNA Apps, all that is required is a web browser and a connection to the internet. Moreover, it takes only a few clicks of the mouse to get the analysis started, and the user interface is as easy as navigating any Web 2.0 (or are we at Web 3.0 already?) website.
During our early-access period, we have received enthusiastic responses specifically regarding usability. We were happiest with the following feedback, which comes from Ganesh K. Boora, a clinician at the Beutler Oncology lab at Mayo Clinic (Ganesh has never run data analysis tools before):
“I am really impressed with the two applications I worked with so far. You have made working with next-gen sequencing data as easy as launching an app on iPhone! The results showed all the relevant and important data in publication ready visuals.”
As Ganesh mentions, the output includes rich, graphical charts and interactive plots that summarize the biologically significant results in a very intuitive manner. Of course, if you are familiar with the standard command-line output of the TopHat/Cufflinks suite, these are faithfully preserved for expert users.
While the RNA-Seq apps have been optimized for use by non-bioinformaticians, labs with deep in-house expertise in informatics have also seen value in the apps. James Hadfield, Director of the Core Lab at Cancer Research UK, had this to say about the new Apps:
"I anticipate using the RNA-seq apps to QC our RNA-seq library preparations before HiSeq sequencing. This should save us time when samples or experiments have gone wrong by quickly pointing to the sample or library prep as the issue.”
Another important use case for expert labs is the routing of samples/ projects to the BaseSpace apps when an unexpected high volume of samples/projects arrive at the lab. Regardless of the specific use case, our early access users have shown that a wide variety of customers can benefit from the RNA-Seq apps.
Fig 1: graphical output of the TopHat Alignment app indicating reads aligned to different regions of the transcriptome.
Fig 2: An interactive scatter plot of gene expression levels. The filters on the left can be used to filter out genes with low control:comparison expression rations, or to perform a Google-style search for specific genes or gene families
Finally, we will soon be releasing the RNAExpress App, which encapsulates the STAR aligner and DESeq in a single, efficient App. This will be the method of choice for rapid expression profiling at the gene level, and is an ideal transition to customers performing microarray based gene expression experiments who want to transition to the digital resolution and efficiency delivered by RNA-Seq.
If you’d like to learn more about BaseSpace Core Apps for RNA, we invite you to visit www.illumina.com/BaseSpaceRNA where you can find a video tour of a typical run-through, a data sheet describing the features and benefits of the App, as well as the user guide for in-depth technical information. The analysis of RNA-seq data has never been easier, and we look forward to showing you why!