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  • RobbenStijn
    Member
    • Feb 2017
    • 12

    Making a coverage track of ZNF778

    Dear all,

    I'm completely new to bioinformatics and I've got a pretty basic question. For Zinc Finger Protein 778 (ZNF778) I am trying to create a coverage track. The problem is that I do not know where to get my information from, which programs to use or how to start.

    I do have some basic programming skills and can work in the terminal and with python.

    Could any of you show me how to do this? It would mean the world to me!

    Regards,

    Stijn
    Last edited by RobbenStijn; 02-21-2017, 02:20 AM.
  • tristan dubos
    Member
    • Dec 2015
    • 39

    #2
    Hi,

    I'm not sure to understand what you want , do you have sequencing data, in this case is it a bam ? ? or you just want some information about you protein ?

    Regards

    Tristan

    Comment

    • RobbenStijn
      Member
      • Feb 2017
      • 12

      #3
      Dear Tristan,

      Sorry for my incomplete information. I obtained some interesting data that I am analyzing though the following link:

      NCBI's Gene Expression Omnibus (GEO) is a public archive and resource for gene expression data.


      An example of how the data of ZNF778 looks is shown below:

      # This file is generated by MACS version 1.4.1 20110627
      # ARGUMENTS LIST:
      # name = ./Processed/peaks/with_control/SI0335
      # format = BAM
      # ChIP-seq file = ./Processed/mapped/SI0335.sorted.nodup.bam
      # control file = ./tmp/macs/SI0335.bkg.bam
      # effective genome size = 2.70e+09
      # band width = 300
      # model fold = 10,30
      # pvalue cutoff = 1.00e-03
      # Large dataset will be scaled towards smaller dataset.
      # Range for calculating regional lambda is: 1000 bps and 10000 bps

      # tag size is determined as 50 bps
      # total tags in treatment: 24340303
      # total tags in control: 50009126
      # d = 150
      chr start end length summit tags -10*log10(pvalue) fold_enrichment FDR(%)
      chr1 9911 10616 706 251 77 60.46 4.07 0.30
      chr1 11119 11740 622 185 32 101.80 10.07 0.13
      chr1 52255 53186 932 236 26 35.90 5.46 0.48
      chr1 713754 714454 701 276 21 32.14 5.20 0.65
      chr1 762008 763537 1530 295 52 75.37 6.63 0.29
      chr1 823169 824143 975 740 37 76.59 5.89 0.28
      chr1 839913 840369 457 311 19 73.91 10.48 0.28
      chr1 851832 853636 1805 1399 85 168.64 10.71 0.07
      chr1 855073 855672 600 269 18 30.24 5.32 0.77
      chr1 856175 857276 1102 400 54 101.63 9.63 0.13

      As you can see, it contains information about MAC peaks, Summits, P-values and FDR(%)-values. I'm interested in creating (or finding) a similar file with the same information, but for another ZNF protein (ZNF675). I am especially interested in the FDR(%) values.

      I hope this is sufficient enough. Thank you very much for your help.

      Regards,

      Stijn

      Comment

      • tristan dubos
        Member
        • Dec 2015
        • 39

        #4
        I think if i understand right your problematic is which tools you can use to calculate your metrics, isn't it ?
        if you want to produce the exactly same result you should use the same tool which produce the file : https://github.com/taoliu/MACS/
        You will need a bam file from a chip-seq if you use this tool , and maybe a bed for the genome region you are interested in (sorry never used this tool ).

        Regards,

        Tristan

        Comment

        • RobbenStijn
          Member
          • Feb 2017
          • 12

          #5
          Thank you Tristan.

          I've got no clue how to use this sort of github files, but I'll try my best.

          Regards,

          Stijn

          Comment

          • tristan dubos
            Member
            • Dec 2015
            • 39

            #6
            You have to download the zip file and uncompressed it and follow the instruction which are in the reads me files. You should care about the dependency

            Tristan

            Comment

            • RobbenStijn
              Member
              • Feb 2017
              • 12

              #7
              Thanks Tristan, that's great!

              Comment

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