SeqGSEA: Gene Set Enrichment Analysis of RNA-Seq Data

[Xi Wang]

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:

http://bioconductor.org/packages/rel...l/SeqGSEA.html

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

[xkcao]

Could you offer an example and describe how to use this package for RNA-seq data analysis?

[Xi Wang]

Could you offer an example and describe how to use this package for RNA-seq data analysis?

Thanks for your message. I have included an example in Section 6 in the package's vignette available at http://bioconductor.org/packages/rel...oc/SeqGSEA.pdf

Any further questions or comments please feel free to let me know. Thanks.

[wilson90]

I am sorry, but it is not available for R version 2.15.1. Is it still available?

[Xi Wang]

The package SeqGSEA started with R version 3.0.0. Perhaps you need to install the latest release of R. If you are not happy with the latest R, and if you are based on Linux platform, you can download the tar ball of the package at

http://www.bioconductor.org/packages/release/bioc/src/contrib/SeqGSEA_1.0.2.tar.gz

and type 'R CMD INSTALL SeqGSEA_1.0.2.tar.gz' to install.

Cheers
Xi

[master_shake]

Using EasyRNASeq for SeqGSEA

The latest vignette claims one can use easyRNAseq for read counts. Using easyRNAseq, should one count exons, or genes? Also, how should the file be outputted, as a summarized experiment? A count table? Normalized values for DESeq?

[Xi Wang]

The latest vignette claims one can use easyRNAseq for read counts. Using easyRNAseq, should one count exons, or genes? Also, how should the file be outputted, as a summarized experiment? A count table? Normalized values for DESeq?

Thanks for checking the latest version of SeqGSEA :-)

You should also count reads on exons, and output the read counts per sample. As to the format, please refer to the files in the directory:

dat.dir = system.file("extdata", package="SeqGSEA", mustWork=TRUE)

Perhaps I will provide an easier way to connect easyRNAseq and SeqGSEA in the upcoming versions.

Cheers
Xi

[wilson90]

Just wondering, what is a geneset file?
How do you define the geneset file?
Any example format?
Thank you.

[Xi Wang]

Just wondering, what is a geneset file?
How do you define the geneset file?
Any example format?
Thank you.

Thanks for considering SeqGSEA.

The gene sets can be downloaded from http://www.broadinstitute.org/gsea/msigdb/index.jsp

Or in GMT format if you want to specify yourself

http://www.broadinstitute.org/cancer/software/gsea/wiki/index.php/Data_formats#GMT:_Gene_Matrix_Transposed_file_format_.28.2A.gmt.29

[Yvone]

I noticed that SeqGSEA uses the object CountDataSet from DESeq. As I am currently using DESeq2, the main object for analyses are DESeqDataSet and cannot be adopted directively in SeqGSEA. I guess these two things are similar, but is there an easy way to transform DESeqDataSet to CountDataSet?

[rpauly]

Sample data available?

Hi,

I came across the SeqGSEA package for GSEA of RNA-seq data.
We extensively work on cancer data sets and found this tool to be quite intriguing.

I was wondering if there is sample data set available to understand all the formats of the file. I am already have the DESEQ count files available.

~Thanks,
Rini

[Xi Wang]

I noticed that SeqGSEA uses the object CountDataSet from DESeq. As I am currently using DESeq2, the main object for analyses are DESeqDataSet and cannot be adopted directively in SeqGSEA. I guess these two things are similar, but is there an easy way to transform DESeqDataSet to CountDataSet?

I will try to move to DESeq2 in the future but at present the most easy way to deal with this issue is just rerun DESeq analysis using the SeqGSEA pipeline. We have already provided one all-in command to go through all analyses.

Cheers
Xi

[Xi Wang]

Hi,

I came across the SeqGSEA package for GSEA of RNA-seq data.
We extensively work on cancer data sets and found this tool to be quite intriguing.

I was wondering if there is sample data set available to understand all the formats of the file. I am already have the DESEQ count files available.

~Thanks,
Rini

A set of example data can be found by executing the following command:
system.file("extdata", package="SeqGSEA", mustWork=TRUE)

[Yvone]

Thanks for your quick reply.

I have other questions.
1). Regarding independent filtering of weakly expressed genes in DE analyses, is it also needed in SeqGSEA?
2). Can I apply multi-factor design in SeqGSEA? In DESeq, I applied glm models to correct variations by other factoers than my interest, for example, calculate DE genes for the treatment while correcting for sex, batch effect. Does SeqGSEA also allow a multi-factor design?

[Xi Wang]

Thanks for your quick reply.

I have other questions.
1). Regarding independent filtering of weakly expressed genes in DE analyses, is it also needed in SeqGSEA?
2). Can I apply multi-factor design in SeqGSEA? In DESeq, I applied glm models to correct variations by other factoers than my interest, for example, calculate DE genes for the treatment while correcting for sex, batch effect. Does SeqGSEA also allow a multi-factor design?

1) I suggestion you feed all genes to SeqGSEA, and SeqGSEA would apply itself filter to exclude unexpressed genes.
2) Sorry with the current version cannot.