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If we are using our own bed file with CNV calls(not using CNVKit), do we need to call cnv_prefilter or is using amplified_intervals.py enough? What additional filtering does cnv_prefilter do?
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Hi Jennifer - thanks for this question - yes, you will need the cnv_prefilter when giving your own calls.
The difference is this: cnv_prefilter.py - check if copy number gains are focal by comparing the copy number segment against the entire chromosome arm to see if it is significantly amplified above what the chromosome arm was called at. amplified_intervals.py - check that these regions of the genome are valid, and not low-complexity, repetitive elements.
If you run your copy number bed file through AmpliconSuite-pipeline.py (formerly PrepareAA.py) and do not set --run_AA and do not set --run_AC it will simply output a file called [sample]_AA_CNV_SEEDS.bed, which will be the focal amplification seed regions after all filters are applied. Hopefully there is no need to dissect the workflow and run the individual scripts in isolation.
If we are using our own bed file with CNV calls(not using CNVKit), do we need to call cnv_prefilter or is using amplified_intervals.py enough? What additional filtering does cnv_prefilter do?
The text was updated successfully, but these errors were encountered: