I'm dealing with quite noisy copy number data from Affymetrix arrays (100K, 500K, etc). It's obvious that resolution of areas of aberration depends on noise and signal-to-noise ratio. The noisier the data, the larger areas can be detected reliably. With the highest noise I probably can reliably get only the whole chromosome loos or gain, but it's ok.
However, many segmentation algorithms I have tried (HMM, CBS, FASeg, etc) do not estimate noise before processing the data, and I have to optimize the parameters almost for every single sample.
Do you know/have experience with an algorithm, which would automate this task? Or what is the best practices for such analysis?