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Parameter tuning and settings
For samples that are expected to have lower than 5% tumor fraction, it may be helpful to modify the default settings to improve parameter estimation. It is recommended to sequence to higher coverages (> 1-5x) for these types of samples. For samples with less than ~0.5% expected tumor fraction, we recommend standard depths of whole genome sequencing (e.g. > 20x).
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Initialize tumor fraction parameter
--normal "c(0.95, 0.99, 0.995, 0.999)"
Initialize the non-tumor (1 minus tumor fraction) to expected values, such as 5%, 1%, 0.5%, 0.1%. ichorCNA will still estimate the tumor fraction but having these initial starting values can help the EM step find better global optima. -
Set initial ploidy to diploid
--ploidy "c(2)"
It will be difficult to predict the ploidy value for low tumor fraction cases. -
Reduce number of copy number states
--maxCN 3
Reducing the state space will help reduce complexity. If you know from a prior sample (e.g. tumor biopsy) that there are large high level copy number events, you can set this to 4. -
Do not account for subclonal copy number events
--estimateScPrevalence FALSE --scStates "c()"
Subclonal events are difficult to detect for low tumor fraction, these can we turned off. -
Train and analyze autosomes only
--chrs "c(1:22)" --chrTrain "c(1:22)"
Exclude chrX in the analysis and training to reduce complexity.