Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • Gene ontology enrichment analysis tool

    Hi All,

    I am working with microarray data. I have some genes of interest that I want to know the GO enriched terms. So far I have found them by GOstat. I also want to know if the representing GO is down/up regulated. Or at least which genes are involving in the representing GO then I can figure it out my self. Do you know any tools that provide me with this?

    Thanks

  • #2
    Have you looked at DAVID: http://david.abcc.ncifcrf.gov/

    Also GenePattern: http://www.broadinstitute.org/cancer...esc/expression
    Last edited by GenoMax; 12-13-2013, 06:52 AM.

    Comment


    • #3
      Yes I have seen david but that one only clusters genes and not Gene ontologies.

      Comment


      • #4
        You may try GAGE if you know R. It works with both microarray and RNA-Seq data.
        GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

        Comment


        • #5
          I am trying to use gage to do a go term analysis on drosophila RNA-seq data.

          All of the vignettes tell very nicely how to find kegg pathway gene sets for different species to do the analysis with but is there a way to get simple go terms for drosophila? I have downloaded the flybase go terms (.fb file) and it seems to be in a very different format than the go.sets.hs and go.subs.hs sets in the vignettes. Is there an easy way to convert these go terms to the appropriate format?

          Comment


          • #6
            Originally posted by bigmw View Post
            You may try GAGE if you know R. It works with both microarray and RNA-Seq data.
            GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.

            http://bioconductor.org/packages/rel...t/doc/gage.pdf
            What is the difference between Heatplus and GAGE? Do you know? I just began to search a tool to do my work and I saw your reply and wonder you might know which one is better.

            Comment


            • #7
              Bioconductor has two annotation data packages: org.Dm.eg.db and GO.db. You may use these two packages to generate the GO gene sets for fly. In other words, you can extract GO term IDs from GO.db, and map the GO terms to Entrez Gene ID using org.Dm.eg.db. Hope this is clear enough.


              Originally posted by evanharrell View Post
              I am trying to use gage to do a go term analysis on drosophila RNA-seq data.

              All of the vignettes tell very nicely how to find kegg pathway gene sets for different species to do the analysis with but is there a way to get simple go terms for drosophila? I have downloaded the flybase go terms (.fb file) and it seems to be in a very different format than the go.sets.hs and go.subs.hs sets in the vignettes. Is there an easy way to convert these go terms to the appropriate format?

              Comment


              • #8
                Gage is a tool for gene set, GO and pathway analysis, it provide functions to visualize the analysi results, like heatmap and scatterplot. Heatplus is a tool dedicated to heatmap plotting. They are not really the same type of tools.
                For more details on gage:
                GAGE is a published method for gene set (enrichment or GSEA) or pathway analysis. GAGE is generally applicable independent of microarray or RNA-Seq data attributes including sample sizes, experimental designs, assay platforms, and other types of heterogeneity, and consistently achieves superior performance over other frequently used methods. In gage package, we provide functions for basic GAGE analysis, result processing and presentation. We have also built pipeline routines for of multiple GAGE analyses in a batch, comparison between parallel analyses, and combined analysis of heterogeneous data from different sources/studies. In addition, we provide demo microarray data and commonly used gene set data based on KEGG pathways and GO terms. These funtions and data are also useful for gene set analysis using other methods.


                Originally posted by wetSEQer View Post
                What is the difference between Heatplus and GAGE? Do you know? I just began to search a tool to do my work and I saw your reply and wonder you might know which one is better.

                Comment


                • #9
                  You may interesting in using clusterProfiler package: http://www.bioconductor.org/packages...rProfiler.html

                  Comment


                  • #10
                    Originally posted by ygc_hku View Post
                    You may interesting in using clusterProfiler package: http://www.bioconductor.org/packages...rProfiler.html
                    Thanks seems so interesting I will look into it.

                    Comment


                    • #11
                      Hi, I'm currently using clusterProfiler for GO enrichment analysis. It is a great tool but I have encountered a problem of inputing data. I read through the manual and find nothing about how to input my own data or what is the format of input data. Could you please shed light on it?
                      Thank you very much!
                      Y

                      Comment


                      • #12
                        Originally posted by angel-sakura View Post
                        Hi, I'm currently using clusterProfiler for GO enrichment analysis. It is a great tool but I have encountered a problem of inputing data. I read through the manual and find nothing about how to input my own data or what is the format of input data. Could you please shed light on it?
                        Thank you very much!
                        Y
                        The input of enrichGO is a vector of entrez gene ID. The manual do explain this.

                        Comment


                        • #13
                          Sorry about my carelessness, I just focused on the scripts when I read the manual.
                          From the example data(geneList), geneList seems to contain two values, one is entrez Id, what about the other one? Is it P-value? If so, does P-value come from the cuffdiff DE results?

                          Thank you!

                          Comment


                          • #14
                            Originally posted by angel-sakura View Post
                            Sorry about my carelessness, I just focused on the scripts when I read the manual.
                            From the example data(geneList), geneList seems to contain two values, one is entrez Id, what about the other one? Is it P-value? If so, does P-value come from the cuffdiff DE results?

                            Thank you!

                            The value is fold change, it can be p-value.

                            The values were used in gene set enrichment analysis for ranking the genes.

                            But for hypergeometric test, only entrez gene IDs are needed.

                            Comment


                            • #15
                              Originally posted by ygc_hku View Post
                              The value is fold change, it can be p-value.

                              The values were used in gene set enrichment analysis for ranking the genes.

                              But for hypergeometric test, only entrez gene IDs are needed.
                              Thank you ! Now I get it working.

                              Cheers

                              Comment

                              Latest Articles

                              Collapse

                              • seqadmin
                                Strategies for Sequencing Challenging Samples
                                by seqadmin


                                Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
                                03-22-2024, 06:39 AM
                              • seqadmin
                                Techniques and Challenges in Conservation Genomics
                                by seqadmin



                                The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.

                                Avian Conservation
                                Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...
                                03-08-2024, 10:41 AM

                              ad_right_rmr

                              Collapse

                              News

                              Collapse

                              Topics Statistics Last Post
                              Started by seqadmin, 03-27-2024, 06:37 PM
                              0 responses
                              12 views
                              0 likes
                              Last Post seqadmin  
                              Started by seqadmin, 03-27-2024, 06:07 PM
                              0 responses
                              11 views
                              0 likes
                              Last Post seqadmin  
                              Started by seqadmin, 03-22-2024, 10:03 AM
                              0 responses
                              53 views
                              0 likes
                              Last Post seqadmin  
                              Started by seqadmin, 03-21-2024, 07:32 AM
                              0 responses
                              69 views
                              0 likes
                              Last Post seqadmin  
                              Working...
                              X