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Old 04-15-2012, 07:05 AM   #1
lix
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Default MNase-seq data analysis

Hi,

Has anyone ever played with the MNase-seq datasets?
I got some mouse datasets running but there seems several points should take into consideration:
1. repetitive region: as about 50% of genome is repetitive sequence and these can arise those multiple alignments during the mapping stage. Generally, only uniquely mapped reads were filtered out for the downstream analysis, which means we lost about 50% region's information of the genome. That's critical if we want to see how about the repeat regions happened in the cell. I don't know if anyone did similar analysis and added the multi-reads and how to process them.
2. input signal: in general ChIP-seq data, the control might generates some peak signal and one of the reason arise this is due to the open chromatin structure. But in this case, say, if I notice the input sharp signal, still, that might be due to the open chromatin in that region, yet might also be generated due to other unknown reason. Has anyone also crush similar problem and how to process them?
3. peak callor choice: there are several peak callers for the mononucleosome calling, I'm just wondering whether MACS can also accomplish this if I'm not only interested in the mononucleosome peaks.

Welcome any kinds of communications and suggestions.
Thanks!

lix
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Old 04-21-2012, 05:13 AM   #2
dawe
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Hello there

Quote:
Originally Posted by lix View Post
2. input signal: in general ChIP-seq data, the control might generates some peak signal and one of the reason arise this is due to the open chromatin structure. But in this case, say, if I notice the input sharp signal, still, that might be due to the open chromatin in that region, yet might also be generated due to other unknown reason. Has anyone also crush similar problem and how to process them?
If you have sharp signals in your input you should find them in IP too. BTW, MNase input should be naked DNA, which is not the same input as in general ChIP-seq data

Quote:
Originally Posted by lix View Post
3. peak callor choice: there are several peak callers for the mononucleosome calling, I'm just wondering whether MACS can also accomplish this if I'm not only interested in the mononucleosome peaks.
If you google for that you may find something. BTW, I'm having good results with DANPOS which is still unpublished. An alternative is NPS. Problem is that you'll need a lot of custom scripts to extract some general information (i.e. phase, distograms, TSS depletion...)

HTH

d
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Old 12-04-2012, 09:19 AM   #3
vkartha
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Quote:
Originally Posted by dawe View Post
Hello there



If you have sharp signals in your input you should find them in IP too. BTW, MNase input should be naked DNA, which is not the same input as in general ChIP-seq data



If you google for that you may find something. BTW, I'm having good results with DANPOS which is still unpublished. An alternative is NPS. Problem is that you'll need a lot of custom scripts to extract some general information (i.e. phase, distograms, TSS depletion...)

HTH

d
Hi, in an attempt to use Danpos using 2 bed tag alignment files as input, I am unable to get it to work correctly, we get the following error:

python2.7 danpos.py tagAlign1-tagAlign2 -k 1
danpos version 2.0.1
command:
python danpos.py tagAlign1-tagAlign2 -k 1

Namespace(bg=None, clonalcut=1e-10, count=None, distance=100, edge=0, extend=80, fs=None, gapfill=0, height=5, keep=1, lmd=300, mafrsz=250, mifrsz=50, name='result', nor='F', paired=0, path='chr22.Gm12878.nuc.tagAlign-chr22.K562.nuc.tagAlign', pcfer=0, smooth_width=20, span=10, statis='P', testcut=1e-05, width=40)
time elasped: 0.36073589325 seconds

normalizing wigs ...
less than 2 datasets, no normalization to be done
saving normalized wigs ...
time elasped: 0.360930919647 seconds

pooling each group ...
Traceback (most recent call last):
File "danpos.py", line 125, in <module>
runDANPOS()
File "danpos.py", line 122, in runDANPOS
smooth_width=args.smooth_width,paired=args.paired)
File "functions.py", line 262, in danpos
pooledgroups[groupname]=groups[groupname].pop(filenames[0])
IndexError: list index out of range

Am I missing something in terms of being able to tell DANPOS that these are the two files I want to compare nucleosomal positioning data on?

Please help, urgent
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