Approximation of Jitter probability in the breakpoints using AEP distribution and confidence masks of SCNA

Jitter is inherent to the breakpoints of measured genome somatic copy number alterations (SCNAs). Therefore, an analysis of jitter is required to reduce errors in the SCNA estimation. The SCNA measurements are accompanied with intensive noise that may cause errors and ambiguities in the breakpoint detection with low signal-to-noise ratios (SNRs). We show that the asymmetric exponential power distribution (AEPD) provides much better approximation to the jitter distribution than the earlier proposed discrete skew Laplace distribution. Furthermore, we confirm that (AEP) distribution its suitable for computing the confidence upper and lower boundary limits in order to guarantee an existence of genomic changes with a required probability. We test some neuroblastoma SCNAs measurements by the upper and lower confidence bound masks with several probabilities.