Seqanswers Leaderboard Ad

Collapse

Announcement

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

  • best pipeline for Chip-seq analysis

    Hi,
    I have Chip-seq data, and I would like to identify the binding sites, peak annotations, and then motif analysis. I came across vast tools for each of the analysis from google.
    I have tried experimenting some of the tools on my data

    Peak Calling - MACS, SISSRS, HOMER-findPeaks

    Peak Annotations - HOMER-annotatePeaks ,peakAnalyzer

    Motif Analysis - HOMER- findMotifs, MEME-CHIP, OPOSSUM-3


    I tried all the above, but I would like to know what others are mostly using and which is the best and highly cited by publications?

    Any suggestions please?

  • #2
    Most of the publications use MACS for peak calling. The motif analysis is a bit tricky. As far as I know there is no 'golden rule' for this task.

    Comment


    • #3
      I should think MACS is the most widespread for detection (excluding those that don't pay for something like Avadis or some other paid-for suite). Then MEME / MEMEchip for the analysis of the regions.

      Comment


      • #4
        But I see that MACS peaks are very broad , in comparison with SISSRS for example.
        Is there anything like after identifying the peak sites by MACS,do I need to use any other tool to minimize the peak lengths ?? I feel that broad peaks makes difficulty in identifying the consensus sites..

        Comment


        • #5
          Well chip peaks can legitimately vary from a few 10s of bases to kilobases and beyond, so it's tricky to say what is 'correct' without knowing more about the dataset. What were you doing the chip for - are you expecting narrow peaks?

          Comment


          • #6
            Originally posted by A.N.Other View Post
            Well chip peaks can legitimately vary from a few 10s of bases to kilobases and beyond, so it's tricky to say what is 'correct' without knowing more about the dataset. What were you doing the chip for - are you expecting narrow peaks?
            I am looking for the transcription factors.. and it is known that most of the motifs for TFS are found mostly around 50-75 bp +/- from the peak center...

            Comment


            • #7
              Originally posted by priya View Post
              But I see that MACS peaks are very broad , in comparison with SISSRS for example.
              Is there anything like after identifying the peak sites by MACS,do I need to use any other tool to minimize the peak lengths ?? I feel that broad peaks makes difficulty in identifying the consensus sites..
              Use the summits.

              Comment


              • #8
                Originally posted by Chipper View Post
                Use the summits.
                Not necessarily quite that simple - I've had macs center peaks in very strange places in some of my datasets in the past, and I'd agree that it's also a bit prone to elongating peaks. Depending on what you're wanting, there are better tools out there.

                Try using findPeaks. It's very good at finding small 'neat' peaks for the sort of thing you're doing.

                Comment


                • #9
                  Originally posted by Chipper View Post
                  Use the summits.
                  I am not aware if this summit .. I see in MACS summit file, the binding sites of one bp . Are summit regions are exact peak centered regions?
                  I came across from the following link how to extract the +/- regions of summits,

                  Comment


                  • #10
                    Originally posted by A.N.Other View Post
                    Not necessarily quite that simple - I've had macs center peaks in very strange places in some of my datasets in the past, and I'd agree that it's also a bit prone to elongating peaks. Depending on what you're wanting, there are better tools out there.

                    Try using findPeaks. It's very good at finding small 'neat' peaks for the sort of thing you're doing.
                    Ok, I check that how it is working with my data, Thank you

                    Comment


                    • #11
                      Originally posted by A.N.Other View Post
                      Not necessarily quite that simple - I've had macs center peaks in very strange places in some of my datasets in the past, and I'd agree that it's also a bit prone to elongating peaks. Depending on what you're wanting, there are better tools out there.

                      Try using findPeaks. It's very good at finding small 'neat' peaks for the sort of thing you're doing.
                      Hi,

                      I would like to have a feedback about findPeaker of Homer.
                      I am using it and also MACS on the same dataset and I found much more peaks with Homer than with MACS (~1500 MACS-peaks and ~150,000 HOMER-peaks)

                      Do you know why?

                      Maybe I need to put some filter on the Homer results or I need to use some options (and not the default?)

                      My data concern a transcription factor, so this is the command line I am using:
                      findPeaks STAT3_NT -style factor -o auto -i INPUT_NT

                      Do you have any experience about this big difference between these results?

                      any suggestions, please?

                      Comment

                      Latest Articles

                      Collapse

                      • seqadmin
                        Current Approaches to Protein Sequencing
                        by seqadmin


                        Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...
                        04-04-2024, 04:25 PM
                      • 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

                      ad_right_rmr

                      Collapse

                      News

                      Collapse

                      Topics Statistics Last Post
                      Started by seqadmin, 04-11-2024, 12:08 PM
                      0 responses
                      30 views
                      0 likes
                      Last Post seqadmin  
                      Started by seqadmin, 04-10-2024, 10:19 PM
                      0 responses
                      32 views
                      0 likes
                      Last Post seqadmin  
                      Started by seqadmin, 04-10-2024, 09:21 AM
                      0 responses
                      28 views
                      0 likes
                      Last Post seqadmin  
                      Started by seqadmin, 04-04-2024, 09:00 AM
                      0 responses
                      53 views
                      0 likes
                      Last Post seqadmin  
                      Working...
                      X