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  • DEXSeq - more than two different conditions

    I am still working on preparing the data for running DEXSeq. I have a question. Will DEXSeq work if there are more than two conditions, e.g. cond1,cond2,cond3.. Thanks!

  • #2
    Yes it will. If you run an analysis with all your conditions, it will show those exons in which at least in one condition is different from the other conditions.

    Comment


    • #3
      DEXSeq with single-end reads

      Is it possible to do a high-quality differential splicing analysis based on single-end reads. Or does it have to be paired-end data. Any views on this are highly appreciated

      Comment


      • #4
        Sure, at least with DEXSeq s it is possible.

        Comment


        • #5
          Originally posted by areyes View Post
          Sure, at least with DEXSeq s it is possible.
          Thanks for your reply. Are you actually one of the developers of DEXSeq?

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          • #6
            Originally posted by sdm View Post
            Thanks for your reply. Are you actually one of the developers of DEXSeq?
            Sorry another question, maybe you can point me to a study/paper, where it has been done by single-end sequencing?

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            • #7
              The original paper has both single-end and paired-end data:

              RNA-seq is a powerful tool for the study of alternative splicing and other forms of alternative isoform expression. Understanding the regulation of these processes requires sensitive and specific detection of differential isoform abundance in comparisons between conditions, cell types, or tissues. W …

              Comment


              • #8
                DEXSeq multiple tissues

                Originally posted by areyes View Post
                Yes it will. If you run an analysis with all your conditions, it will show those exons in which at least in one condition is different from the other conditions.

                Hello,
                I have 37 RNA-seq datasets for 18 human tissues - some have 3 replicates, some 2 and some do not have any (sorry to say that).

                I'm thinking of a way to do differential exon usage analysis - using DEXseq.

                I could not see any example in the documentation where multiple conditions are compared (eg., tissues) other than pairwise comparisons. In edgeR, I was able to use the ANOVA-like test for getting differentially expressed genes (across an average of all 18 tissues). I was wondering if there is such a test I could do with DESeq/DEXseq.

                Thanks,
                Manoj.

                Comment


                • #9
                  Originally posted by areyes View Post
                  Yes it will. If you run an analysis with all your conditions, it will show those exons in which at least in one condition is different from the other conditions.
                  Hello everybody,

                  I have RNA-Seq paired-ends data for 3 conditions: Control (4 biological replicates), Leukemic cells with mutation in gene X (6 biological replicates) and Leukemic cells without mutation in gene X (4 biological replicates).

                  One of the questions I try to answer is the differential exon usage induced by this mutation. I am using DEXSeq_1.8.0.

                  Basically, I need to compare exon level in leukemic cells with and without the mutation.
                  Since I have additional information with the control, I would like to output the genes that show a differential expression in at least one exon between both conditions leukemic cells with and without the mutation, with in addition the level for the controls.
                  To be clear, I don't want to see the genes that show a differential expression in at least one exon between conditions leukemic cells with or without the mutation and the control.

                  Is it possible with DEXSeq?
                  If not, I have 2 choices: either I "loose" the information from the control condition or I see all the changes including those that do not come from the mutation (that's what I did for now).

                  Thank you in advance,
                  Jane

                  Comment


                  • #10
                    Hi @Jane M,

                    You could try to change the GLM formulas to include all the variables of your analysis. First, I would recommend updating your R and DEXSeq version. if your design data frame looks like this:

                    Code:
                    phenotype   mutatedGene
                    control   no
                    control   no
                    control   no
                    control   no
                    leukemia   yes
                    leukemia   yes
                    leukemia   yes
                    leukemia   yes
                    leukemia   yes
                    leukemia   yes
                    leukemia   no
                    leukemia   no
                    leukemia   no
                    leukemia   no
                    you could try to include the formulas:

                    Code:
                    formulaFullModel <- ~ sample + exon + phenotype:exon + mutatedGene:exon
                    formulaReducedModel <- ~ sample + exon + phenotype:exon
                    And proceed as in the section "Additional technical or experimental variables" of the vignette

                    Comment


                    • #11
                      Originally posted by areyes View Post
                      you could try to include the formulas:

                      Code:
                      formulaFullModel <- ~ sample + exon + phenotype:exon + mutatedGene:exon
                      formulaReducedModel <- ~ sample + exon + phenotype:exon
                      Yes, good idea! I will try within next days. I did not think about my problem this way, thank you!

                      Comment


                      • #12
                        Thinking about it again, I am not sure what will be the output of the testing. To add the "phenotype" as a blocking factor we would also need samples with phenotype "control" and mutatedGene "yes". Of course this is not possible in this experiment! How do the "plotDEXSeq" plots look like?

                        Maybe would be good to try to use the "formulaFullModel" to estimate dispersions, and the testing doing ignoring the "phenotype" variable...

                        Let me know what comes out!

                        Comment


                        • #13
                          full formula

                          Hi Alejandro,
                          I have one condition with :
                          CTRL
                          CTRL
                          CTRL
                          CTRL
                          H24
                          H24
                          H48
                          H48

                          Can I use the defalut full formula?
                          Where can I found exons for H24-CTRL and H48-CTRL as result?
                          Thanks
                          Jose

                          Comment


                          • #14
                            Hi Jose,

                            The default formula would test for differences in exon usage in any of the conditions.

                            If you are interested in the specific changes between H24-CTRL and between H48-CTRL it is better to subset the data accordingly and run the analysis separately.

                            Alejandro

                            Comment


                            • #15
                              Thanks Alejandro,
                              I thought something similar to to what Mike uses in DESeq2 could be used in DEXSeq but with exons behind is harder.
                              I'll subset the two and do it separately.

                              Jose

                              Originally posted by areyes View Post
                              Hi Jose,

                              The default formula would test for differences in exon usage in any of the conditions.

                              If you are interested in the specific changes between H24-CTRL and between H48-CTRL it is better to subset the data accordingly and run the analysis separately.

                              Alejandro

                              Comment

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