Comments (2)
The copy numbers are relative to the specified ploidy (default 2) -- they are still log2 ratios with the same interpretation as the segmentation output (.cns). This is so that you can plot the .absoluteCN.cns file with the scatter
/heatmap
/diagram
commands the same way you would with the original .cns file. The call
command just rounds the segment means to what they would be if the true copy number were an integer.
To get the absolute integers in a human-readable form, try:
cnvkit.py export bed sampleName.absoluteCN.cns --show-neutral
The thresholds work like this (see cnvlib.call.absolute_threshold ):
if log2 <= -4.3: CN=0
if log2 <= -1: CN=1
if log2 <= 0: CN=2
if log2 <= 0.6: CN=3
...
So the germline thresholds, rounding to the nearest log2(integer), could be calculated like:
> log2( (0:4 + .5 ) / 2)
[1] -2.0000000 -0.4150375 0.3219281 0.8073549 1.1699250
Sorry for the confusion. I'll update the docs.
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Thank you very much! It is clear now.
Javier
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Related Issues (20)
- Installation error HOT 7
- Unable to produce .cnr files HOT 2
- Getting BAF and allelic imbalance in export vcf
- Improper post-processing of segment [bug]
- Unable to use fix without antitarget file for WGS samples
- Merging segments while running pipeline
- `segment` function fails HOT 1
- Somatic CNV calling in case of pre-existing CNVs
- Installation problems HOT 5
- Unable to load BED file with skgenome
- cnvkit.py segment error
- CNVkit segment command RuntimeError: Subprocess command failed HOT 1
- access command: recommended -s (mingap) value
- Blank plots HOT 1
- Possible bug in bin sizes
- segment with cbs method - threshold
- call with filters cn, ci, sem
- Filtering single-cell false positive calls
- targeted DNA seq
- Proper read pairs
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