Unconfigured Ad

Collapse
X
 
  • Filter
  • Time
  • Show
Clear All
new posts
  • dekontrol
    Junior Member
    • Oct 2012
    • 8

    MACS: ChIP and control with different tag size

    Hi,
    I am using MACS2 for ChIP-seq peak calling.

    I have a treatment file with original reads of 51bp. Before alignment, the reads were dynamically trimmed on 3'end for removing low quality bases (with Trimmomatic software). At the end, aligned reads ranges from 42 to 51 bp.

    Then, I have a control (input) file with original reads of 36 bp. Before alignment, the reads were dynamically trimmed on 3'end for removing low quality bases (with Trimmomatic software). At the end, aligned reads ranges from 30 to 36 bp.

    If I let MACS to automatically determine the tags size, MACS comes out with a wrong number. Moreover, since I think MACS scan only the first n reads, MACS does not give the average of the tags length.

    So, I have to specify the tag size with the option --tsize. However, it is impossible to set a tsize for the treatment and a different tsize for the input.

    What do you think is the best solution for this situation?

    Thanks very much!
    Albert
  • dpryan
    Devon Ryan
    • Jul 2011
    • 3478

    #2
    Why didn't you sequence the IP and input at the same time? I'm guessing that you also didn't construct the libraries at the same time and therefore have an uncontrolled batch effect completely confounding your results.

    Comment

    • dekontrol
      Junior Member
      • Oct 2012
      • 8

      #3
      In the real world, sometimes you have to use old data with new data, or data that comes from different labs.. any idea?

      Comment

      • SylvainL
        Senior Member
        • Feb 2012
        • 180

        #4
        Even if I fully agree with dpryan, it happened to me that researchers really wanted to use their old datasets with a new one. Except that in my case, both samples were done with the same chromatin then fragments sizes were similar. I just trimmed the longest reads to fit the shortest...
        Hope both samples (treatment and control) were obtained with the same chromatin (I mean same sonicated chromatin, not only from same celltype...)

        If not, maybe the best would be to use MACS without control for both samples and then you crossed the results yourself...

        Comment

        • dekontrol
          Junior Member
          • Oct 2012
          • 8

          #5
          Yes SylvainL, I am exacly in that situation: my wets wanted to use their old data.

          Is there any paper that I can give to my wets, where is clearly stated that treatment and input should comes from the same chromatin?

          Thanks guys for your help!

          Comment

          • dpryan
            Devon Ryan
            • Jul 2011
            • 3478

            #6
            They need a paper for that? They would have the exact same problem with their wet lab experiments. It'd be like taking an image of a Western blot from a paper and comparing the raw band intensities to one of your own Westerns. In fact, just use that example, since they should understand it.

            Comment

            • dekontrol
              Junior Member
              • Oct 2012
              • 8

              #7
              They told me that they think that they can make only one input from the same cell type, and use it as a reference input for all the future experiments from the same cell type..

              Comment

              • dpryan
                Devon Ryan
                • Jul 2011
                • 3478

                #8
                Funny, so they must think that they only ever need to run 1 Western as a baseline for comparisons then too...

                Comment

                • SylvainL
                  Senior Member
                  • Feb 2012
                  • 180

                  #9
                  So typical when wet-biologists do not understand a technique... I had to deal with some of these quite recently. Then, we finished the discussion by me telling them: if you want to perform only one Input, then prepare a huge batch of chromatin... They didn't like this comment when they realized they would have to prepare 1000 plates together

                  If they don't understand the example of dpryan (they may argue that it depends of the exposure of the blot, etc...), simply ask them to summarize all the Ct they obtained for their control genes in qPCR (all same cell type of course) let's say the last 4 years....

                  Comment

                  Latest Articles

                  Collapse

                  • GATTACAT
                    Reply to Nine Things a Sample Prep Scientist Thinks About Before Sequencing
                    by GATTACAT
                    Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.
                    Yesterday, 11:43 AM
                  • SEQadmin2
                    Nine Things a Sample Prep Scientist Thinks About Before Sequencing
                    by SEQadmin2


                    I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.

                    Here are nine questions we think about, in roughly the order they matter, before...
                    06-18-2026, 07:11 AM
                  • SEQadmin2
                    From Collection to Sequencing: Why Sample Preparation and Preservation Define Sequencing Data
                    by SEQadmin2


                    Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.


                    The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
                    ...
                    06-02-2026, 10:05 AM

                  ad_right_rmr

                  Collapse

                  News

                  Collapse

                  Topics Statistics Last Post
                  Started by SEQadmin2, 06-30-2026, 05:37 AM
                  0 responses
                  9 views
                  0 reactions
                  Last Post SEQadmin2  
                  Started by SEQadmin2, 06-26-2026, 11:10 AM
                  0 responses
                  18 views
                  0 reactions
                  Last Post SEQadmin2  
                  Started by SEQadmin2, 06-17-2026, 06:09 AM
                  0 responses
                  52 views
                  0 reactions
                  Last Post SEQadmin2  
                  Started by SEQadmin2, 06-09-2026, 11:58 AM
                  0 responses
                  110 views
                  0 reactions
                  Last Post SEQadmin2  
                  Working...