Comments (3)
Good point. It would be nice for the batch command to behave more like make
. In the meantime I suggest running the analysis like this:
-
batch
with a flat reference on all "normal" samples, treating them as tumor samples:cnvkit.py batch *_Normal.bam -n -d normals/ ...
cnvkit.py heatmap normals/*.cns -o heatmap_normal_flatreference.pdf
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Examine the heatmap of the output .cns files to see which "normal" samples have problematic CNVs and should be excluded.
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Build a reference from the selected normals:
cnvkit.py reference normals/{1,2,4,5,7}_Normal.*.cnn -f hg19.fa -o real_reference.cnn
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Use that reference to process the tumor samples
cnvkit.py batch *_Tumor.bam -r real_reference.cnn -d normals/ ...
Alternatively, you can process all of the BAMs as normals, or tumors with a flat reference, and use the reference
and fix
commands directly to finish the analysis.
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Thanks for the detailed instructions, Eric. I'll be sure to make use of them.
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See also #81 - now an error is raised instead of processing the same sample twice. (Still suboptimal, but we're working on it.)
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Related Issues (20)
- 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
- cnvkit.py coverage does not honor -q option
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