Question: Define exact peak borders
0
gravatar for ATpoint
2.4 years ago by
ATpoint25k
Germany
ATpoint25k wrote:

Hello,

I would like to ask if there is an implementation to define peak borders. To make it more clear, see this screenshot. I have some reference region from another assay (blue bar on top). Within this region, I check the signal of a second assay (blue peak profile). The question is now if there is a simple solution to define the peak borders (red bar) automatically. MACS does this nicely with the --nomodel option, but as it checkes the input data for significances etc. it does not output all the regions I am interested in. Is there a standalone solution for this task?

peak calling macs • 569 views
ADD COMMENTlink modified 2.4 years ago by Charles Plessy2.7k • written 2.4 years ago by ATpoint25k

To clarify: you want the red bar to be the same length as the blue bar or as the blue peak region?

What about peak center +/- total fragment length?

More importantly....what is the purpose of defining the borders? what are you trying to achieve by doing this?

ADD REPLYlink modified 2.4 years ago • written 2.4 years ago by YaGalbi1.4k

The read bar is what I printed in by hand, but I would like to get it automatically, based on the shown peak profile. I have a list of mutations. Many of them are within the blue-bar region, but outside of the actual peak signal (so the read bar). In order to exclude these, I would like to have exact borders, in order to exclude these passengers.

ADD REPLYlink written 2.4 years ago by ATpoint25k

Why was this thread deleted?

ADD REPLYlink written 2.4 years ago by WouterDeCoster42k

Don't know?! Not on purpose

ADD REPLYlink written 2.4 years ago by ATpoint25k

Odd, well, I restored it...

ADD REPLYlink written 2.4 years ago by WouterDeCoster42k
0
gravatar for Charles Plessy
2.4 years ago by
Charles Plessy2.7k
Japan
Charles Plessy2.7k wrote:

There are many alternative peak callers, but among them perhaps you can have a look at paraclu.

Since it outputs nested clusters, you can define by yourself a threshold that corresponds to granularity that suits the most your analyses. Also, you can run it in a way that all the data will be part of at least one cluster (unlike in the example above, where a small peak is left out).

ADD COMMENTlink written 2.4 years ago by Charles Plessy2.7k

I will check it out, thank you. Cluster within cluster seems to be pretty much what I need.

ADD REPLYlink modified 2.4 years ago • written 2.4 years ago by ATpoint25k
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