Hi Liu,

That is good to know some one is doing similar stuff as mine. 

I was going to through 2-3 papers which described to get a comprehensive 
list of CNVs it is better to consider a CNV which is called in 2 or more 
CNV calling algorithms. This is what I have observed recently in some 
papers too. Please let me know if you want link for the papers I am talking 
about. I currently do not have them but will email you links for the papers.



On Tuesday, January 20, 2015 at 5:01:46 PM UTC+1, Chengyu Liu wrote:
>
> Hi Sam,
>
> I am doing similar stuff with you. I also need to identify regions which 
> are amplified or deleted. I have paired samples. 
> There are quite many different ways to define gain and loss of a segment. 
> It is a tricky question. 
>
> From the literature search, it seems best to call CNVs using from 
>> different softwares to have a comprehensive list before doing association 
>> analysis. For this reason, I need to know gain or loss of DNA in a segment. 
>>
> I did not get your point.  
>  
>
>> When I tried GLAD on just 3 samples, it took more than 30 minutes to 
>> finish. 
>>
> My experience is that CBS is faster than GLAD. When I ran GLAD with 4 
> samples, it took like two or more to finish them.  
>
>>
>> I don't know how to incorporate this segments from CBS in to my analysis. 
>> Please let me know if you have any ideas on how to solve this.
>>
> You can replace GLAD model with CBS model (cns <- CbsModel(dsT, dsN)where 
> dsN is average of all the controls).
> http://aroma-project.org/vignettes/pairedTotalCopyNumberAnalysis/ 
> <http://www.google.com/url?q=http%3A%2F%2Faroma-project.org%2Fvignettes%2FpairedTotalCopyNumberAnalysis%2F&sa=D&sntz=1&usg=AFQjCNFXCJHW_UqojQMDh5FW1xbPLguBPA>
>

  I was actually thinking about this. Wow this solves my problem. Thanks a 
lot mate for this information.  

>
>
>
> Do you need to identify copy number alterations (CNA)? or Just copy number 
> variants(CNV)? I need to identify CNA not CNV. For now I do not know how. 
> Do you know also how to map amplified or deleted region to genes?  If you 
> know something about it, happy to hear.
>

I am lost here. Is there difference between CNA and CNV?



> Br,
> C.Y
>
>  
>
>>
>> Thanks,
>>
>> Best Regards,
>> Sam.
>>
>> On Tuesday, January 20, 2015 at 10:38:27 AM UTC+1, Chengyu Liu wrote:
>>>
>>> Hi,
>>>
>>> On Monday, January 19, 2015 at 3:42:59 PM UTC+2, Sam Padmanabhuni wrote:
>>>>
>>>> Dear AromaAffymetrix Team,
>>>>
>>>> First of all, thank you very much for such a detailed vignette on how 
>>>> to perform the CNV analysis. 
>>>>
>>>> I am Sam, a PhD student in genetics, working on CNV analysis on data 
>>>> from CytoScan HD Array. I have read the vignette to do CRMAv2 and 
>>>> non-paired CBS. I have copied the commands and ran in R.
>>>>
>>>> But, I have few questions regarding CbsModel and GladModel in 
>>>> segmentation algorithm:
>>>>
>>>> 1. It is mentioned that, copy number states is not calculated in 
>>>> CbsModel segmentation. How do I get information of whether the segment is 
>>>> a 
>>>> loss or gain from output of CbsModel? I mean can this information be 
>>>> passed 
>>>> to other algorithms to estimate copy number state.
>>>>
>>> As far as I know, the out put of CBS is the relative copy number.  It 
>>> does not directly tell you the copy number states. 
>>>
>>>>
>>>> 2. I have looked in to GLAD model and it is mentioned that it is 
>>>> developed for aCGH but my data is not from aCGH. Can it be still used to 
>>>> calculate copy number states for the data I am working on?
>>>>
>>> GLAD can calculate copy number states for affy-array, although I have 
>>> not used it before.
>>>
>>>>
>>>> 3. Also, do you have a vignette on how to run CRMAv2 and CBS on 
>>>> CytoScan HD array? This would be really helpful.
>>>>
>>> It is the same with other chiptype, prepare input as required (there is 
>>> vignette).
>>>
>>>
>>> BTW, I am also working on CytoScan HD. What kind of analysis are you 
>>> going to do? Do you have paired samples or non-paired? Maybe we have 
>>> something common and we can discuss.
>>>
>>> Br,
>>> C.Y
>>>
>>>
>>>
>>>> Thank you,
>>>>
>>>> Best,
>>>> Sam.
>>>>
>>>>
>>>>
Best Regards,
Sam.  

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