Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • Qualitative comparison of different RNA-Seq experiments

    Hi,

    I'm trying to do a qualitative comparison of publicly available RNA-Seq datasets from different bacteria. Given that the growth conditions are comparable is it possible, e.g. based on RPKM, to make a qualitative comparison of expression levels of conserved genes?

    Cheers,
    Tim

  • #2
    What do you think the problems might be?

    Comment


    • #3
      I'm not sure how to compare them. Usually I'd go with something like edgeR or similar for DE analysis. But in this case I'm not sure if that's suitable because it's different bacteria, different experimental setups etc. Therefore, I guess it's more a "gene A of orgA relatively highly expressed, in organismB it's not" ... but what normalization/approach to us? Does that make my problem more clear?

      Tim

      Comment


      • #4
        You are, indeed, going to have the problems you mentioned.
        The data is from various sources, prepared differently, using different methods, on different machines analyzing expression for sequences that , though conserved, are different sequences.

        Comparing them with deep certainty about the results is going to be challenging.

        Back in the day, I remember some guys using all the CEL files for Affymetrix expression chips and comparing expression between the various expressions from various sources in NIH's GEO (gene expression omnibus) database. A lot easier with a single chip type and single manufacturer's recommended procedure.

        This EdegeR or DESEQ type approach are good for getting a measure of expression differences, that's not your problem.

        The noise and biases of the various methods used to create the reads is your problem.

        Perhaps limiting data to the best/most used protocols and sequencing machine might a good approach.

        Comment


        • #5
          Maybe you should compare pairs

          You're going to stumble into many normalization issues here. I'm having trouble comparing experiments from the same lab in two different experimental settings, let alone different labs and bacteria.
          I would try another approach using simple statistics. I assume you have enough replicates so you can pair the experiments, taking the two conditions in each bacteria, growth phase, lab etc. and in each pair determine, for each gene, if it was up or down regulated (you'll have to normalize them, using DESeq normalization or other method). Then, if you have about 15 (or even less, depends on the number of genes you're testing) such pairs you can run the sign test on each gene. You should get p-values with sufficient power even after FDR correction.

          Comment


          • #6
            If it were me, I would not even try to merge the two datasets. Analyze each independently just as you would any other cross-species comparison. Pull out your two independent gene lists and look for the overlap between them. Then you can make some comparisons of the commonly detected differential expression in each. First thing I'd want to see is do the two gene lists even rank order correlate at all. You can then do some stats if you wished to compare the independently derived gene lists.
            Michael Black, Ph.D.
            ScitoVation LLC. RTP, N.C.

            Comment


            • #7
              Thanks everybody.
              The "simple stats" solution is what I was thinking of, too. I will have a look into sign test and rank order conservation. Thanks for the help so far.

              Comment

              Latest Articles

              Collapse

              • seqadmin
                Strategies for Sequencing Challenging Samples
                by seqadmin


                Despite advancements in sequencing platforms and related sample preparation technologies, certain sample types continue to present significant challenges that can compromise sequencing results. Pedro Echave, Senior Manager of the Global Business Segment at Revvity, explained that the success of a sequencing experiment ultimately depends on the amount and integrity of the nucleic acid template (RNA or DNA) obtained from a sample. “The better the quality of the nucleic acid isolated...
                03-22-2024, 06:39 AM
              • seqadmin
                Techniques and Challenges in Conservation Genomics
                by seqadmin



                The field of conservation genomics centers on applying genomics technologies in support of conservation efforts and the preservation of biodiversity. This article features interviews with two researchers who showcase their innovative work and highlight the current state and future of conservation genomics.

                Avian Conservation
                Matthew DeSaix, a recent doctoral graduate from Kristen Ruegg’s lab at The University of Colorado, shared that most of his research...
                03-08-2024, 10:41 AM

              ad_right_rmr

              Collapse

              News

              Collapse

              Topics Statistics Last Post
              Started by seqadmin, Yesterday, 06:37 PM
              0 responses
              8 views
              0 likes
              Last Post seqadmin  
              Started by seqadmin, Yesterday, 06:07 PM
              0 responses
              8 views
              0 likes
              Last Post seqadmin  
              Started by seqadmin, 03-22-2024, 10:03 AM
              0 responses
              49 views
              0 likes
              Last Post seqadmin  
              Started by seqadmin, 03-21-2024, 07:32 AM
              0 responses
              67 views
              0 likes
              Last Post seqadmin  
              Working...
              X