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