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  • rachita
    Junior Member
    • Mar 2013
    • 7

    MedIp-seq Input data

    HI Everyone,

    I am analysing MedIP-seq data from adipose tissue and there are control and treated samples. But there is no "INPUT SET" available. Is there any way I can get the analysis done without the input set. Can I use the control data as INPUT set ?
  • asurarocks
    Member
    • Nov 2010
    • 12

    #2
    If you are using MEDIPS package, INPUT sample is optional. I got decent numbers of DMRs without using input sample.

    Comment

    • rachita
      Junior Member
      • Mar 2013
      • 7

      #3
      Thanks for your reply.

      Comment

      • mikep
        Member
        • Feb 2011
        • 45

        #4
        It appears it's not only optional, but actually ignored for the purpose of DMR analysis with the builtin edgeR

        Why is that? Wouldn't some kind of input subtraction prior to differential analsyis be preferable?

        Comment

        • tanaybhatt
          Junior Member
          • Apr 2017
          • 3

          #5
          Can someone direct me to a published paper where DMR analysis has been done without taking the input in consideration (or without input subtraction/normalization)?

          Comment

          • rachita
            Junior Member
            • Mar 2013
            • 7

            #6
            Our data which was why the question was posted is not published. Here is the link "http://dx.doi.org/10.1080/21623945.2017.1320002". You can check that.
            Last edited by rachita; 05-03-2017, 07:22 AM.

            Comment

            • asurarocks
              Member
              • Nov 2010
              • 12

              #7
              Here you go:
              Cells alter their gene expression in response to exposure to various environmental changes. Epigenetic mechanisms such as DNA methylation are believed to regulate the alterations in gene expression patterns. In vitro and in vivo studies have documented changes in cellular proliferation, cytoskeletal remodeling, signal transduction, bone mineralization and immune deficiency under the influence of microgravity conditions experienced in space. However microgravity induced changes in the epigenome have not been well characterized. In this study we have used Next-generation Sequencing (NGS) to profile ground-based “simulated” microgravity induced changes on DNA methylation (5-methylcytosine or 5mC), hydroxymethylation (5-hydroxymethylcytosine or 5hmC), and simultaneous gene expression in cultured human lymphoblastoid cells. Our results indicate that simulated microgravity induced alterations in the methylome (~60% of the differentially methylated regions or DMRs are hypomethylated and ~92% of the differentially hydroxymethylated regions or DHMRs are hyperhydroxymethylated). Simulated microgravity also induced differential expression in 370 transcripts that were associated with crucial biological processes such as oxidative stress response, carbohydrate metabolism and regulation of transcription. While we were not able to obtain any global trend correlating the changes of methylation/ hydroxylation with gene expression, we have been able to profile the simulated microgravity induced changes of 5mC over some of the differentially expressed genes that includes five genes undergoing differential methylation over their promoters and twenty five genes undergoing differential methylation over their gene-bodies. To the best of our knowledge, this is the first NGS-based study to profile epigenomic patterns induced by short time exposure of simulated microgravity and we believe that our findings can be a valuable resource for future explorations.

              Comment

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