Question: about the runs with cn.mops
0
gravatar for Bogdan
20 months ago by
Bogdan550
Palo Alto, CA, USA
Bogdan550 wrote:

Dear Gunter, 

good morning and a happy autumn time ! when you have a minute, i would like to ask for an advice regarding the output of cn.mops on tumor-germline samples :

i've been using the algorithm that you have developed on approx 100 tumors that have a germline counterpart, and now I would like to better understand the results.

It would be great if you could tell me more about the differences between the functions : 

-- segmentation()

-- cnvs() 

-- cnvr()

 

For example, for chr21, after segmentation, we obtained the regions : 

"seqnames" "start" "end" "width" "strand" "sampleName" "median" "mean" "CN"

"chr21" 1 12050000 12050000 "*" NA 0 0.0028 "CN2"

"chr21" 12050001 12140000 90000 "*" NA 1.0224545205372 2.1378 "CN3"

"chr21" 12140001 12870000 730000 "*" NA 0 -0.2329 "CN2"

"chr21" 12870001 46709983 33839983 "*" NA 1.19917489022848e-64 0.0135 "CN2

 

After cnvs() function : 

"chr21" 12050001 12140000 90000 "*" "CN3

 

After cnvr() function : 

"chr21" 12050001 12140000 90000 "*" "CN3"

 

And, what do "median" and "mean" fields represent, after segmentation() ?

It would be very helpful to hear from you, and many thanks in advance, 

-- bogdan

cn.mops referencecn.mops • 543 views
ADD COMMENTlink modified 20 months ago • written 20 months ago by Bogdan550
Answer: about the runs with cn.mops
3
gravatar for Günter Klambauer
20 months ago by
Austria
Günter Klambauer540 wrote:

Hello Bogdan,

 

  • Slot "segmentation": This contains the whole chromosome split into adjacent windows by breakpoints. This means that the initial windows, in which you counted the reads (e.g. 1000 bp), are joined to form longer segments. For each segment and sample, the inferred copy number is reported.
  • Slot "cnvs": A subset of segments from the ones from the segmentation slot. The segments that meet the criteria to be a copy number variation (CNV), i.e. being above or below the given thresholds, are contained in this slot.
  • Slot "cnvr": Whereas "segmentation" and "cnvs" report per sample, this slot reports CNVs per population. This means that this is a kind of single linkage clustering of the CNVs. Typically, CNVs of individuals occur frequently at similar locations in the genome. Therefore, I report the regions where any CNV occurs.

I hope this helps with the interpretation.

Regards,

Günter

ADD COMMENTlink modified 20 months ago • written 20 months ago by Günter Klambauer540

Dear Gunter, thanks a lot for a very prompt reply. If I may add another question please :

-- sometimes, in the file produced by the "segmentation" there are a few segments labelled as CN2 . For the case of tumor-normal comparison, what does it mean ? Is it related to potential LOH in the germline sample ?

-- and, how shall i interpret the "median" and "mean" numerical values, after segmentation() ? We are running the cn.mops algorithm on tumor-normal pairs, per chromosome. 

thanks a lot,

-- bogdan

 

 

 

ADD REPLYlink written 20 months ago by Bogdan550
1

The segmentation slot contains also normal ("CN2") segments, i.e. segment that do not contain a copy number variation. So, you should expect to find CN2 there.

The "median" and "mean" are the median and mean signed individual I/NI (sI/NI) calls across the joined segments (cn.mops supplies and sI/NI call for each of the initial segments). The higher the values, the higher the underlying copy number, the lower, the lower the copy number.

ADD REPLYlink written 20 months ago by Günter Klambauer540

Dear Gunter, thank you again ;) I would like to better understand the differences between the results from CNVS() versus the results from CNVR(), in the context of CNV calling on TUMOR-GERMLINE, and if you do not mind providing some insights on another question below please.

 

ADD REPLYlink modified 20 months ago • written 20 months ago by Bogdan550
Answer: about the runs with cn.mops
0
gravatar for Bogdan
20 months ago by
Bogdan550
Palo Alto, CA, USA
Bogdan550 wrote:

Dear Gunter,

please, it would be helpful, if I could have your insights on the following results. I have been running cnMOPS on TUMOR-GERMLINE sample, and for a particular case (on chr 11):

-- cnvs() function gives the results (below), that contain a combination of CN1, CN3, and CN4

chr11
124660001
126440000
1780000
*
NA
-1
-0.9855
CN1
chr11
126440001
127240000
800000
*
NA
0.5849625007
0.5846
CN3
chr11
127240001
128050000
810000
*
NA
0.5849625007
0.7208
CN3
chr11
128050001
130720000
2670000
*
NA
0.9999844562
0.8221
CN4
chr11
130720001
134030000
3310000
*
NA
0.5849625007
0.7167
CN3
chr11
134030001
134960000
930000
*
NA
1
1.0069
CN4
chr11
134960001
135086622
126622
*
NA
0.5849625007
0.6648
CN3

-- while for the same regions, cnvr() gives only 1 "concatenated" region, that is a CN1 :

chr11
124660001
135086622 10426622 * CN1
                 
                 
                 
                 
                 
                 
                 
ADD COMMENTlink written 20 months ago by Bogdan550
1

Hello Bogdan,

You should go with the CNVs in the slot "cnvs()". The integer copy numbers in the slot "cnvr()" are the average integer copy numbers in the whole region. Since the region is larger than the individual CNVs, in fact the region is a union of all CNVs that occur there, the average copy number is typically CN2 again.  What is reported in "cnvr()" is a kind of summary because users find it convenient to be pointed to locations in the genome, where copy number variations occur frequently. However, the actual results can be found in "cnvs()".

 

Regards,

Günter

 

ADD REPLYlink modified 20 months ago • written 20 months ago by Günter Klambauer540

Dear Gunter, thank you for your message and for confirmation. Yes, I thought that this may be the case, and we've used indeed the results from cnvs().

ADD REPLYlink written 20 months ago by Bogdan550
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