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  • Venn diagram for DE data?

    Does anyone know of a free software package that would allow me to produce a venn diagram based on the differential expression values obtained from a cufflinks>cuffdiff analysis? (or even using just the raw RPKM/FPKM values)

    It doesn't need to be anything fancy just allow the quantification of each individual quadrant withing the diagram.

    Any pointers in the right direction would be great

    Thanks

  • #2
    How many circles in the Venn Diagram?

    Either way, you can do this in R (with simple areas, or trying to scale the areas to match the counts). I wrapped the R limma package's Venn Diagram function for up to 3 circles as a Galaxy Tool, see http://toolshed.g2.bx.psu.edu

    Comment


    • #3
      That's great thank you

      Comment


      • #4
        Venn diagram R, cuffdiff data

        Hi All,

        I am interested in learning how to do a 2-way venn diagram in R from a table generated with cuffdiff data. I have tried a few times but i get no where - my R skill are not that good. I am uploading some dummy data to see if you guys can give me a hand with this.
        I guess my first question would be: can you do a venn diagram from the data attached?
        I want to see how many genes are differentially expressed in the control (CTR, value_1) vs the treatment (TRT, value_2) anf in both (CTR and TRT)

        Thanks!

        -G
        Attached Files

        Comment


        • #5
          Firstly, you should post this as a new question.

          Secondly, never use anything other than an actual txt file. What you uploaded is a bloated RTF file, which is an absolute pain to use for anything real. RTF (like a word document or excel) is only meant to look at, not to actually use for anything important.

          Finally, what you're trying to do makes no logical sense. There's no such thing as differentially expressed in both CTR and TRT. That's not even a coherent concept.

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          • #6
            Originally posted by dpryan View Post
            Finally, what you're trying to do makes no logical sense. There's no such thing as differentially expressed in both CTR and TRT. That's not even a coherent concept.
            Had an impression that I was reading my Supervisor's email.
            Hope you didn't offend the guy who asked :-)

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            • #7
              Originally posted by Sergioo View Post
              Had an impression that I was reading my Supervisor's email.
              Hope you didn't offend the guy who asked :-)
              To be frank, anyone offended by that won't want to stay in science. Compared to the grilling one gets by a PhD committee or after a talk at a conference, that was pretty nice

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              • #8
                Originally posted by dpryan View Post
                To be frank, anyone offended by that won't want to stay in science. Compared to the grilling one gets by a PhD committee or after a talk at a conference, that was pretty nice
                IMO, science does not need such committees and those remarks are less helpful.
                Believe me, Ph.D student that perform well are not those with harsh advisors.

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                • #9
                  how to draw venn diagram

                  Dear all,
                  what i am about to ask is one insanely easy question, but i need an instruction.
                  some people draw venn diagram for the results of their transcriptome blast against different database; and some people analyze there DEG by using different tools like DESeq, baySeq, edgeR, and illustrate the analysis overlapping rate of the DEGs with the venn diagram . what tools can do that jobs ? especially for the latter.

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                  • #10
                    You might want to try Vennt to create Venn Diagrams: http://drpowell.github.io/vennt/

                    PS: I have used Vent before and it works fairly well from my own experience.

                    Comment


                    • #11
                      biovenn

                      venny 2.0

                      Comment


                      • #12
                        thanks @Zapages and @Chipper , i will check both of them.

                        Comment


                        • #13
                          If you have multiple contrasts in a CuffDiff file, you can import/load that directly into iPathwayGuide and it will analyze each contrast in the context of genes, predicted miRNA, GO terms, Pathways, and diseases, plus it will perform a meta analysis between the contrasts and show you a venn diagram with overlapping regions for each of the analyses.

                          Best of all it's completely free to try.

                          Here's a screen shot showing overlapping DEGs. You can see on the right side we also show the logFC of the selected gene in each contrast.

                          Comment


                          • #14
                            Originally posted by AndrewO View Post
                            Best of all it's completely free to try.
                            Wouldn't "it's completely free(period)" actually be best of all?

                            Comment


                            • #15
                              Originally posted by kmcarr View Post
                              Wouldn't "it's completely free(period)" actually be best of all?
                              In a way it is - but we are a company, so... there is that.

                              We allow people to upload and run as many datasets as they desire for as long as they want - that costs nothing (except your time). The results are available to view for 72 hours. There is no limit, and it's completely free (period).

                              If you like the report and want to keep the results, then you have the option to purchase the report and keep it forever. If you don't like it or don't want it beyond the 72 hours, it will automatically expire.

                              Give it a try. You can learn more at www.AdvaitaBio.com

                              Here's a different screenshot showing the perturbation of a pathway and the expected distribution of those values.

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