Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • bigwig and replicates dilemma

    Hi guys!

    I am visualizing bigwig files on the genome viewer (I use IGV) from RNAseq samples of human origin.
    I have two clusters of 10 replicates each. I wanted to have just the experimental vs control track (otherwise it'll be too big screenshot, and also too confusing), but I am not sure what would be the good way to produce accurate data.

    Should I use samtools merge to combine all the replicates from group#1 and group#2 (: all experimental combined and all control combined), and use those .bam files as input to create bigwig files? Or is there any other way?

    Thanks to all!!!

    Manu

  • #2
    The ideal way to visualize this might be a box and whisker type plot using coverage values.

    5 wiggles (wig) or big wigs overlaid as plots representing (for each genomic location) the summary values for the samples as 5 wiggle lines: the 5 lines would be
    1) max, 2) min, 3) lower quartile, 4) upper quartile and 5) median for the TEST CASES.

    If you had controls, another 5 lines (in another color) could represent such CONTROLS CASES.

    Calculating it is pretty straightforward but I don't know if IGV or UCSC custom would handle it.
    Last edited by Richard Finney; 08-18-2014, 02:03 PM.

    Comment


    • #3
      It sounds messy to me to have 5 wiggles (or 10) overlaid. In my experience this is hard to interpret. I would personally just average the wiggle files and have test and control tracks separated. Its just a visualization track. The more meaningful statistics of the expression will be in DE test tables and what not, not in a browser view.

      You should be able to use wig.math from here (https://github.com/timpalpant/java-genomics-io) to do that averaging.

      Comment


      • #4
        Originally posted by Wallysb01 View Post
        It sounds messy to me to have 5 wiggles (or 10) overlaid. In my experience this is hard to interpret. I would personally just average the wiggle files and have test and control tracks separated. Its just a visualization track. The more meaningful statistics of the expression will be in DE test tables and what not, not in a browser view.

        You should be able to use wig.math from here (https://github.com/timpalpant/java-genomics-io) to do that averaging.

        Hi Wallysb01 and Richard,

        thanks for your reply!
        I agree that it is just a visualization tool...but some of the recent papers I have read on similar topics include a table with the genome browser screenshot of some DE genes. Although it's not a validation of DE - you also need to do qPCRs of course- it might be a nice thing to add to your paper.
        What do you think about that?

        thanks indeed for the advices, I will try wig.math!

        Manu

        Comment


        • #5
          Hi, good question!

          I have only 2x2 samples, but ran into the same "problem". 4 tracks seperated or overlayed do not give a nice picture. And thats what you want to have. As already mentioned, its only for visualization of the statistical correct, abstract table data.

          I use IGB and used the build in graph options, which can create an averaged multigraph from selected graphs. I used my normalized wig files for this and overlayed the 2 resulting tracks.

          Comment

          Latest Articles

          Collapse

          • seqadmin
            The Impact of AI in Genomic Medicine
            by seqadmin



            Artificial intelligence (AI) has evolved from a futuristic vision to a mainstream technology, highlighted by the introduction of tools like OpenAI's ChatGPT and Google's Gemini. In recent years, AI has become increasingly integrated into the field of genomics. This integration has enabled new scientific discoveries while simultaneously raising important ethical questions1. Interviews with two researchers at the center of this intersection provide insightful perspectives into...
            02-26-2024, 02:07 PM
          • seqadmin
            Multiomics Techniques Advancing Disease Research
            by seqadmin


            New and advanced multiomics tools and technologies have opened new avenues of research and markedly enhanced various disciplines such as disease research and precision medicine1. The practice of merging diverse data from various ‘omes increasingly provides a more holistic understanding of biological systems. As Maddison Masaeli, Co-Founder and CEO at Deepcell, aptly noted, “You can't explain biology in its complex form with one modality.”

            A major leap in the field has
            ...
            02-08-2024, 06:33 AM

          ad_right_rmr

          Collapse

          News

          Collapse

          Topics Statistics Last Post
          Started by seqadmin, 02-28-2024, 06:12 AM
          0 responses
          28 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 02-23-2024, 04:11 PM
          0 responses
          74 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 02-21-2024, 08:52 AM
          0 responses
          82 views
          0 likes
          Last Post seqadmin  
          Started by seqadmin, 02-20-2024, 08:57 AM
          0 responses
          69 views
          0 likes
          Last Post seqadmin  
          Working...
          X