Originally posted by pogaora
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Originally posted by Chipper View PostLooks like you have a contamination from an exome capture study?
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looks a little bit too systematic.
is the gene you show in the browser a gene that someone working close to you just maxi-prepped? could it be a very trivial wetlab contamination? me, e.g., i work in drosophila and whatever ChiP I generate and whatever other labs do ip the white gene is always bound (exons only) as it is the favorite marker gene..
if not i would anyway immediately do a qPCR validation and check a different antibody in case one is available.
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Originally posted by JohnK View PostAre you sure your gene-model is for the right build you're using?
Are you sure the gene exists?
CCDS may be a good way of making sure you don't include erroneous gene predictions.
You may have a signal, but you under-sequenced- what's your MSERR?
You may not have a signal.
You could use MEME and SamTools to build your consensus sequences, crop them and look for motifs; with MEME.
I'd like to hear more about this as I am interested now.
We´re happy with the gene model and the existence/expression of the gene in these cells.
However, your point about under-sequencing is well taken. Our yield of alignable reads was low (total of about 5 million alignable reads from 2 replicates). What is MSERR?
The attached pdf of UCSC tracks shows what we´re talking about. I missed the scale on the left of the top track - it goes up to 6 (six) compared with the scale on the bottom track which goes to 73. The Input control was used in peak calling.
The peak calling software did in fact call the first peak (on the left of the fig) as a peak but none of the others.
We plan to use MEME to look at generating a motif but need to decide what regions to feed it first.
CheersAttached Files
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Are you sure your gene-model is for the right build you're using?
Are you sure the gene exists?
CCDS may be a good way of making sure you don't include erroneous gene predictions.
You may have a signal, but you under-sequenced- what's your MSERR?
You may not have a signal.
You could use MEME and SamTools to build your consensus sequences, crop them and look for motifs; with MEME.
I'd like to hear more about this as I am interested now.
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just to get you right: you "see" the peak but the peak finding software does not find them?
if yes: don't trust your eyes
what is the scaling of input and IP signals when you look in the browser, what are your total read numbers in IP and input?
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Originally posted by mudshark View Posta) did you include the input as a background control in your peak calling procedure?
b) are you sure that your antibody is specific?
c) did you validate some of the exonic peaks using qPCR?
d) did you test if the peaks in exons are enriched for the consensus binding motif of your TF?
The input was included when we called the peaks, although having said that, this is a feature that we observe when visualising the data on UCSC browser (lots of reads piling up in the ChIP sample with nothing in the input) rather than being peaks called with a low FDR by the software. Did I mislead readers with the term peak?!
The antibody is ChIP certified by the vendors and specific so far as we can see.
We haven´t done any validations yet - we´re still trying to get a handle on what are likely to be ´real´ enriched regions.
We don´t have a reliable motif for this TF. Known targets are very scarce.
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a) did you include the input as a background control in your peak calling procedure?
b) are you sure that your antibody is specific?
c) did you validate some of the exonic peaks using qPCR?
d) did you test if the peaks in exons are enriched for the consensus binding motif of your TF?
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Originally posted by mudshark View Postdid you perform a control sequencing reaction - input or mock? transcribed regions are in general over-represented in chromatin preps and tend to attract peak calls if controls are not included in the analysis.
Yes, we did an input control which left out the IP step.
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did you perform a control sequencing reaction - input or mock? transcribed regions are in general over-represented in chromatin preps and tend to attract peak calls if controls are not included in the analysis.
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we had the same situation as well when we use tags to do the CHIP
Originally posted by pogaora View PostHi,
We have some ChIP-seq data which targetted a transcription factor in human cells. We have found that in a lot of cases we see peaks lining up with exons. Has anybody else found this and anyone know why it might happen?
Cheers.
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ChIP-seq peaks map to exons
Hi,
We have some ChIP-seq data which targetted a transcription factor in human cells. We have found that in a lot of cases we see peaks lining up with exons. Has anybody else found this and anyone know why it might happen?
Cheers.Last edited by pogaora; 01-11-2011, 07:39 AM.Tags: None
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