Any one using SeqMonk to do ChIP seq analysis? I found it super easy to use and come with some handy analysis after peak generation, e.g. filter functions. But I don't know what's statistical model behind the peak calling. The program seems not published, so I wonder data generated with this program is acceptable by journals?
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I didn't even know it exists
Looks nice, I'll try ASAP. -
SeqMonk (at least in it's current version) doesn't have a peak detection algorithm as such built in - although you can certainly use the quantitation tools for doing this kind of work.
If your ChIP data is pretty clean with isolated clusters of sequences then you can use the contig probe generator to build probes over clusters of reads. We've used this successfully with traditional ChIP based experiments. The probe generation is not statistically based, but done simply from building contigs of overlapping reads.
For ChIP samples which are much noisier and have reads over much of the genome you're normally better generating tiled probes over the whole genome and then using the window based filters to identify peaks.
For identifying significant enrichments you can either use the distribution based filters or statistical filters such as the boxwhisker filter.
As for why SeqMonk isn't published yet - well it's on my list of stuff to do (but it's far from alone on there!)Comment
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The immune system’s power comes from its genetic diversity, allowing myriad threats to be neutralized through first recognizing foreign antigens. That diversity is also what makes the immune system so difficult to study. Recent advances in sequencing technology and computational biology, however, are giving researchers new tools to understand immune responses and immune-related diseases in greater detail.
This convergence of genetics, immunology, and computation...09-01-2026, 05:41 AM
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