Unconfigured Ad

Collapse
X
 
  • Time
  • Show
Clear All
new posts
  • JenyaD
    Junior Member
    • Mar 2018
    • 2

    #1

    chip-seq data analysis with galaxy

    Hi all! I am very new to this field, so I apologize in advance for my ignorance. I have done several chip-seq experiments on a protein from A.thaliana that functions in homologous recombination. I am struggling a lot with analyzing my data, mostly because I do not completely understand how the tools work. I use galaxy to do the analysis, Bowtie and MACS.

    I have several questions regarding these tools, hopefully someone will help!
    1. I know MACS provides the peak scores as -10log(pvalue) and it gives me ranges usually from 50-3100. But how does MACS2 calculate the score? Using the same dataset, I get very narrow ranges usually in single digits.
    2. What do treatment wig and control wig files show? I read that they show the binding signal, however this explanation is way to vague for me. And how can I correlate the peak bed file to the bigwig file on a genome browser?
    3. When I use MACS to call the peaks, I use default setting (pvalue cutoff 1e-5, and MFOLD value of 32). However, MACS fails everytime since it cannot find enough paired peaks to build the shifting model. Lowering the MFOLD value does not help. Only when I choose not to build the shifting model, only then will MACS succeed in calling the peaks. But, now I am worried, can I trust these peaks that MACS called? If it cannot make a shifting model, how could I predict the location of the binding site? I leave the arbitrary shift size 100 bp, but how do I know if this is the proper value to use? I also read that MACS cannot build the shifting model since there is no defined peaks, this can be a result of broad peaks (like for RNApol), it looks like my peaks are broad as well.

    Thank you for your help!!!!

Latest Articles

Collapse

  • SEQadmin2
    16S/ITS Profiling vs. Shotgun Metagenomics: What Changes in Your Workflow?
    by SEQadmin2




    NGS has revolutionized clinical microbiology by offering new ways to identify and surveil pathogens without prior knowledge of the target. One popular approach is 16S rRNA and ITS amplicon sequencing, which targets specific microbial markers. But studies are increasingly incorporating shotgun metagenomics, a technique that sequences all DNA from a sample without targeting specific microbial markers. This approach allows more detailed taxonomic classification, detection...
    10-30-2026, 06:46 AM
  • SEQadmin2
    Multiomic Liquid Biopsy: What DNA/RNA Panels Reveal That DNA Alone Can’t
    by SEQadmin2



    Tumors contain complex mixtures of cell populations that evolve in response to treatment and host-specific factors. Tissue biopsies provide only static snapshots of a tumor’s state. But what if we could follow that evolution over time using a minimally invasive technique?

    Liquid biopsies can detect tumor-derived material circulating in the bloodstream, providing a way to study treatment response, detect emerging resistance, and discover new biomarkers. Circulating
    ...
    10-14-2026, 09:55 AM

ad_right_rmr

Collapse

News

Collapse

Topics Statistics Last Post
Started by SEQadmin2, 10-28-2026, 09:57 AM
0 responses
45 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 10-28-2026, 09:51 AM
0 responses
26 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 10-22-2026, 11:13 AM
0 responses
74 views
0 reactions
Last Post SEQadmin2  
Started by SEQadmin2, 10-22-2026, 10:48 AM
0 responses
48 views
0 reactions
Last Post SEQadmin2  
Working...