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  • SeqGSEA: Gene Set Enrichment Analysis of RNA-Seq Data

    I am glad to introduce to you guys a new Bioconductor package, SeqGSEA, developed by our group. The detailed description of this package is:

    SeqGSEA: Gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. Using negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Statistical significance of each gene set investigated is reached by subject permutation. Based on the permutation, statistical significance regarding to each gene's differential expression and splicing can also be achieved , respectively.

    The package can be accessed at the URL:
    The package generally provides methods for gene set enrichment analysis of high-throughput RNA-Seq data by integrating differential expression and splicing. It uses negative binomial distribution to model read count data, which accounts for sequencing biases and biological variation. Based on permutation tests, statistical significance can also be achieved regarding each gene's differential expression and splicing, respectively.


    Should you have any questions, comments, or suggestions, please feel free to email me at (xi.wang (at) newcastle.edu.au). Thanks.
    Xi Wang

  • #2
    Just in case some of you didn't see the original post :-)
    Xi Wang

    Comment


    • #3
      Xi,

      Can SeqGSEA be used with Drosophila data?

      I run into a problem with my genesets. I've tried Ensemble gene IDs and gene symbols, but none pass the initial size filter. It gives the following error on GSEnrichAnalyze:

      Error: all(i <= size(x)) is not TRUE

      Thanks.

      Comment


      • #4
        Originally posted by elgarcia View Post
        Xi,

        Can SeqGSEA be used with Drosophila data?

        I run into a problem with my genesets. I've tried Ensemble gene IDs and gene symbols, but none pass the initial size filter. It gives the following error on GSEnrichAnalyze:

        Error: all(i <= size(x)) is not TRUE

        Thanks.
        Hi Can you describe your problem in more details, including information such as how your gene IDs look like and what kind of gene set data you have, and can you send them to me via email: [email protected]

        Thanks
        Xi
        Xi Wang

        Comment

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