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Functional Annotation
What tool does everyone use to annotate ChIP-Seq peaks (i.e. nearest gene, etc). Is there a linux source I could download somewhere for it?
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I suggest either:
a. Galaxy's "Operate on Genomic Intervals": http://main.g2.bx.psu.edu/
or
b. BEDTools (admittedly my own command-line software). You would download genes and whatever annotations you are interested in (BED format) and then use the tools to find closest genes (closestBed), etc.
bedtools.googlecode.com
Aaron -
Aaron,Originally posted by quinlana View Post
Can BEDtools find insersections in more than 2 bed files? For example, if I am doing ChIP-Seq for Factor A, B, C, & D and I want a single bed file telling me all the places enriched for all of the factors or 3 out of 4 etc.Comment
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Hi,Originally posted by RockChalkJayhawk View Post
BEDTools cannot do what you ask in a single command. However, there are multiple ways to do this with a couple commands. I demonstrate two possible solutions below (assuming I understood you correctly).
Based on your example, let's assume you have four BED files, each representing regions of enrichment for A, B, C, and D, respectively.
The following command will return all of the regions enriched for A that overlap (by at least 1bp) with regions enriched for B,C and D. The "-u" returns a unique entry even when multiple overlaps are found
You could then mix and match commands like this to capture all possible situations.Code:$ intersectBed -a A.bed -b B.bed -u | \ intersectBed -a stdin -b C.bed -u | \ intersectBed -a stdin -b D.bed -u > ABCD.bed
An alternate and perhaps simpler way is to count the number of overlaps between A/B, A/C, A/D. The example below assumes each BED file has 6 columns (chrom, start, end) and the fourth column (hence the cut -f 4) is the count of overlaps b/w A and B which is returned by the "-c" option.
# Count the overlaps b/w A and the others. Every entry in A will have a count. It will be 0 if there were no overlaps
# Now, let's paste the counts to the end of the A entriesCode:$ intersectBed -a A.bed -b B.bed -c | cut -f 4 > AtoB.counts $ intersectBed -a A.bed -b C.bed -c | cut -f 4 > AtoC.counts $ intersectBed -a A.bed -b D.bed -c | cut -f 4 > AtoD.counts
Now you will have something that looks like this:Code:$ paste A.bed AtoB.counts AtoC.counts AtoD.counts > AwithCounts.bed
The first entry says that this A interval was also enriched in C and D, but not B.Code:chr1 100 200 0 2 1 chr1 200 300 1 1 2 ... chrY 100 200 0 0 0
The second entry says that this A interval was also enriched in all 3 others.
The third entry says that this A interval was not enriched in any others.
You would repeat for B, C and D and could then write a basic awk or perl script to ask your questions with such an output.
There are other ways to tackle this and obviously subtleties to the questions asked, but I hope this helps you get the ball rolling, as it were.
AaronComment
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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 -
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
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