Can Geneious handle RNA-Seq data?

In Geneious R9 we have introduced the 'Geneious for RNA seq' assembler for mapping RNA-seq reads to a reference sequence.  This assembler can discover novel introns and map ends of reads correctly around these novel introns, or it can map reads to introns via CDS, mRNA or junction annotations on your reference sequence.  This assembler will also discover fusion genes.

For Geneious R8 and earlier you can also use the Geneious Map to reference assembler to assemble RNA-seq data but you will need to increase the maximum gap size and maximum allowed gaps per read under the Advanced options to account for the likely size of your introns.  Geneious also has a plugin for the Tophat RNA-seq mapper, which works with Geneious versions 7.0 and above. 

The Geneious de novo assembler will also assemble RNA-seq data, but be aware that the assembler is not specifically designed to handle transcriptome data and won’t take alternative splicing and differences in coverage levels into account when producing an assembly. 

Geneious R8 and later contains tools for digital gene expression analysis, allowing you to calculate normalized expression measures TPM, RPKM and FPKM on reference mappings of individual samples, and to compare values between two samples to find differentially expressed genes.  To calculate TPM, RPKM and FPKM for individual samples, select your reference assembly and go to "Calculate Expression Levels" under the Annotate and Predict menu. The results are displayed as a heat map annotation track on the reference sequence.  To compare two samples you must first run Calculate Expression levels on the reference assemblies for each sample (which must have the same reference sequence), then click Save to apply the results track to the reference sequence document.  Then select the reference sequence and go to "Compare Expression Levels" under the Annotate and Predict menu.  For more information, please see the Geneious User Manual (PDF or online).

post updated Nov 2015

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Comments

  • Avatar
    Rogerb

    You can use geneious to do digital gene expression analysis if you:

    1) Map the sequence reads to an annotated genome

    2) Use the annotate and predict menu to "Find High/Low coverage" . Tell it to only find in "Annotations in the reference sequence of type CDS" and find regions with coverage above (0 or 1 or perhaps some other threshold if you wish). 
    The above will provide a table of the average coverage per gene.  Of course this ignores intergenic regions and it doesn't provide separate data for reads that map in each orientation ( a feature which would be handy for directional RNA-seq).  However, if you chose to annotate intergenic regions, the same method can be used to get read coverage for those (or any other regions).  The output is normalized to the length of the gene already since it's the average number of reads per bp.

  • Avatar
    Hilary Miller

    We also now have a plugin for the Tophat RNAseq mapper, which you can run on linux or mac with Geneious 7.0.3 and above.  

  • Avatar
    Jeff Bickmeier

    Any additional capability of note since the Feb posting on the Tophat RNAseq mapper?  Anything that can be run on PC with Geneious?

  • Avatar
    Hilary Miller

    We don't have anything more in the works for RNAseq at this stage.  Unfortunately we can't configure Tophat to run on Windows because of the way its source code is written.  

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    Bsguida

    I wish I was a good enough Java programmer (Or had the time to re-learn Java) but it seems it should be pretty straight forward (for someone JAVA-minded) to write a plugin to generate some useful quantitative RNA-seq (Prokaryotic) data using Geneious (I have a Pro-license for it and wish it was more useful for transcriptomics as this is the current "omics" boom).  Most of the architecture is already in place.  Using an annotated reference genome (with at minimum a Glimmer CDS annotation track), a read mapper (Bowtie/Tophat), and then integrating that with a program like Cufflinks should enable Geneious to generate a GUI displaying differential gene expression data for RNA-Seq.  But even without using cufflinks, the data for differential expression quantification is already present in Geneious.  The average number of reads per CDS, the length of each CDS, and the sequencing depth are all known to Geneious, perhaps a plugin with directly calculates the RPKM for a set of selected CDS or generates a table of RPKM values for all annotated CDS.  A new metric for RNA-Seq data is the transcripts per million (TPM) calculation which seems to be more robust and just as easy to calculate, perhaps a plugin that give you the choice between the two, or simply gives you both values.  Please JAVA gods, write this plugin for Geneious, it's going to be the key to the software's survival :)

  • Avatar
    Matt Kearse

    Thanks for your feedback. We took it on board and implemented some basic expression analysis functionality in Geneious 8.0.1. This is available now as a beta version from http://www.geneious.com/download-beta

    See Hilary's updated message at the top of this page for more information. Please give it a go and let us know whether or not you find it useful.

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    Joshua Koh

    I think Geneious really needs to up its game in RNAseq capabilities. Really hope that the next major release version 10 will implement some much needed tools like differential genes heatmap, volcano plots, venn diagrams and the ability to account for biological replicates. Ideally, implementation of either EdgeR or DESEQ2 algorithms will be sufficient. I am hoping that I would not have to migrate to other bioinformatics software or learn codes in R to do all these things......

  • Avatar
    Hilary Miller

    These features won't be in R10 as other areas of development are currently taking priority.  However we're aware of the need for these tools and hope to make improvements to our RNAseq functionality in future.