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  • DESeq2 questions

    Hello, I have a function data sets. I want to look at which functions are over-representative. However, I am only interested in a subset of functions for example DNA synthesis.

    Can I just use the functions related to DNA synthesis (subset table) to do the DESeq2 analysis or I have to use the whole dataset and later found which over-representative functions relative to DNA synthesis?

    Thanks,
    Last edited by SDPA_Pet; 03-27-2017, 08:05 AM.

  • #2
    Are you mixing up differential expression analysis (DESeq2) with GO term enrichment analysis (e.g. GeneSCF)?

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    • #3
      Originally posted by GenoMax View Post
      Are you mixing up differential expression analysis (DESeq2) with GO term enrichment analysis (e.g. GeneSCF)?
      Well, I don't think so, because DESeq2 can give you log2 fold change of each functions and whether the change significant or not.
      Last edited by SDPA_Pet; 03-27-2017, 08:18 AM.

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      • #4
        Originally posted by SDPA_Pet View Post
        Can I just use the functions related to DNA synthesis (subset table) to do the DESeq2 analysis or I have to use the whole dataset and later found which over-representative functions relative to DNA synthesis?
        You should use the whole dataset and later on check if the genes up and down regulated correspond to a certain function.

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        • #5
          DESeq2 expects raw read-level count data as input. I don't expect that it would be possible to get that from a function data set.

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          • #6
            Originally posted by gringer View Post
            DESeq2 expects raw read-level count data as input. I don't expect that it would be possible to get that from a function data set.
            Hey guys, I am sorry about the confusion. The dataset that I use the gene counts dataset. (The gene coding for the functional genes).

            So, should I use the subset or total dataset.

            Comment


            • #7
              @SDPA_Pet: I think you have metagenomics data that you have somehow mapped as counts --> a function (so not a specific gene). Is that interpretation correct? That may be important for other posters to know.

              In any case cherry picking data is not the way to go with DESeq2.

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              • #8
                Originally posted by GenoMax View Post
                @SDPA_Pet: I think you have metagenomics data that you have somehow mapped as counts --> a function (so not a specific gene). Is that interpretation correct? That may be important for other posters to know.

                In any case cherry picking data is not the way to go with DESeq2.
                Right? It's kind of tricky? In our field, we the conception of gene/functions are exchangeable.Anyhow, it is just counts table.

                Just curious,GenoMax? What is difference between the gene table and function table in your field (I would guess your field is biomedical field)? Do you have an example?

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                • #9
                  DESeq2 is not operating on the identifiers but is considering the counts associated with them.

                  Code:
                  DNA_synthesis      50
                  TCA_Cycle        100
                  OR
                  Code:
                  BRCA1      50
                  TRPV1        100
                  should produce equivalent results from DESeq2.

                  Comment


                  • #10
                    Right, my questions about the dataset choosing.

                    In you example, let say DNA_systhesis total have 50 counts. I can go deeper hierarchical level
                    DNA systhesis

                    sub Function 1 5
                    sub function 2 3
                    ...

                    TCA total 100
                    sub Fucition 1 5
                    sub fuction 2 3

                    ....

                    I could choose two way to do this. First, use the total datasets which is 150 functions total, and look at which sub function related to DNA synthesis is overabundant.

                    Or, I could only extract the 50 subfunctions from DNA synthesis and run DEseq to find out which one is overabundant.

                    To me, I only care about one large category. However, the sample size wouldn't be same in the two different analyses

                    Originally posted by GenoMax View Post
                    DESeq2 is not operating on the identifiers but is considering the counts associated with them.

                    Code:
                    DNA_synthesis      50
                    TCA_Cycle        100
                    OR
                    Code:
                    BRCA1      50
                    TRPV1        100
                    should produce equivalent results from DESeq2.
                    Last edited by SDPA_Pet; 03-28-2017, 07:52 AM.

                    Comment


                    • #11
                      You may want to post this question on Bioconductor DESeq2 support site where people with the statistical chops will answer (someone on here may do that as well).

                      Comment


                      • #12
                        Originally posted by GenoMax View Post
                        You may want to post this question on Bioconductor DESeq2 support site where people with the statistical chops will answer (someone on here may do that as well).
                        Can you give the link? I google it and find different sites. Not sure which one is the authentic

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                        • #13
                          Originally posted by SDPA_Pet View Post
                          Can you give the link? I google it and find different sites. Not sure which one is the authentic
                          Here is the bioconductor support site. Tag your question with deseq2.

                          Comment


                          • #14
                            Originally posted by GenoMax View Post
                            Here is the bioconductor support site. Tag your question with deseq2.
                            Hi GenoMax,

                            Thanks. BTW, do you know is there any good forum to discuss R application. Bioconductor.org focus on molecular bioinformatics. I need some forums such as help people with plots (ggplots 2), multivariate statistics, etc.

                            Comment

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