Entering edit mode
6.2 years ago
jomo018
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720
I sometimes receive a BED file as a result from some experiment (for example peak list of some factor) and try to figure out if and what is special in these regions. Is there a "common denominator"? So I am checking for motifs, GO/Pathway of nearest genes, enrichment in, say, enhancers, comparison with TF ChIP-Seqs etc...This is not systematic and definitely non exhaustive.
Can anyone suggest a tool, set of tools, pipeline or even a paper that tries to address this, less-than-well-defined challenge in a systematic manner? The goal is to stay objective and detach the pipeline from the original reasoning behind the creation of the BED file.
I would consider this an innately unstructured activity, I wouldn't expect any general "pipeline" to be useful.
What do you mean by "common denominator" ? Don't they, whoever gave you the peak list, tell you what factors are chip'd?
If you know which factors/histone changes are chip'd, you can put the genomic regions into some biological context. With this peak list, we are largely reducing the search space on genome to find relevant regions that likely give some hints about the condition under study.
"Peak list of some factor" was just for clarification. The experiments are more complex. Therefore in the goal statement, I am trying to shy away from original biological context.