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  • Is there any good statistic way or tools to compare the read count

    Is there any good statistic way or tools to compare the read count difference between treatments?

    The data is per-base sequencing read count, and we don’t know the exact distribution of the per-base read count (attached).

    For example:
    2 treatments (treatment1 & treatment2), 3 samples (biological repeat) in each treatment.

    data table:
    chrom position treatment1_1 treatment1_2 treatment1_3 treatment2_1 treatment2_2 treatment2_3
    chr12 26229353 1 245 175 0 0 1
    chr14 60833709 120 0 81 0 0 1
    chr2 87516663 1 111 83 0 1 0
    chr14 60802415 101 0 61 0 0 1
    chr11 60356985 17 37 24 0 0 1
    chr1 18300478 14 34 24 1 0 0
    chr1 271501486 29 28 12 1 0 0
    chr15 75932698 32 25 11 0 0 1
    chr1 188326280 14 24 28 1 0 0
    chr7 43038815 16 37 11 1 0 0
    chr20 48971845 23 18 22 0 0 1
    chr13 50030361 10 37 16 0 1 0
    chr5 58346829 9 35 18 1 0 0
    chr14 60803076 74 0 107 0 0 0
    chr15 21554556 33 44 19 0 0 0
    chr21 8881378 30 51 14 0 0 0
    chrX 56348140 0 51 40 0 0 0
    chr24 22387291 30 43 16 0 0 0


    The aim is to know if there is significant difference between treatment1 and treatment2, a p value will be needed. Of course, if a FDR is also available, that will be fantastic.

    Many thanks!
    Attached Files
    Last edited by owwa; 04-18-2014, 06:27 PM.

  • #2
    How can i post a question on this forum?

    How can i post a question on this forum?

    Comment


    • #3
      @owwa: One of the normal RNAseq programs (DESeq2, edgeR, etc.) will likely work. They expect reads counts like your and use a negative binomial model, which is likely what you need anyway.

      @man4ish: If you click on one of the forums you'll see a "New Thread" button on the left side above the posts.

      Comment


      • #4
        Originally posted by dpryan View Post
        @owwa: One of the normal RNAseq programs (DESeq2, edgeR, etc.) will likely work. They expect reads counts like your and use a negative binomial model, which is likely what you need anyway.

        @man4ish: If you click on one of the forums you'll see a "New Thread" button on the left side above the posts.
        Many thanks to dpryan!

        But my data is per-base read count, not like the RNAseq one. It is possible that the distribution of these two types of read count is different. I don't know if there is some tools or programs which are specific to per-base data.

        Comment


        • #5
          Originally posted by man4ish View Post
          How can i post a question on this forum?
          Hi!
          It's unfortunately an annoying page design:
          Click on forums,
          Choose a topic,
          At that page, at top-left (or around there), you will see a box says "New Thread". That is how you post a new question.

          Comment


          • #6
            Originally posted by rnaeye View Post
            Hi!
            It's unfortunately an annoying page design:
            Click on forums,
            Choose a topic,
            At that page, at top-left (or around there), you will see a box says "New Thread". That is how you post a new question.
            yes,
            1). go to: http://seqanswers.com/forums/index.php

            2). select a topic, such as "Bioinformatics"

            3). click the button "New Thread" (top-left of the page)

            4). fill in your question title, content..., then submit.

            Comment


            • #7
              Originally posted by owwa View Post
              Many thanks to dpryan!

              But my data is per-base read count, not like the RNAseq one. It is possible that the distribution of these two types of read count is different. I don't know if there is some tools or programs which are specific to per-base data.
              Yes, it's possible that your case follows a different distribution, but likely not. The only way to find out is too look at the data and try to see what distribution it follows.

              Comment


              • #8
                Thank you dpryan, your suggestions is very helpful.

                Comment

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