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Jitter Approximation and Confidence Masks in Simulated SCNA Using AEP Distribution

  • Jorge Ulises Muñoz–Minjares
  • Yuriy S. ShmaliyEmail author
  • Luis Javier Morales–Mendoza
  • Osbaldo Vite–Chavez
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10633)

Abstract

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 used to guarantee an existence of genomic changes with a required probability. We test some simulated SCNAs measurements by the upper and lower confidence bound masks with several probabilities.

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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Jorge Ulises Muñoz–Minjares
    • 1
  • Yuriy S. Shmaliy
    • 1
    Email author
  • Luis Javier Morales–Mendoza
    • 2
  • Osbaldo Vite–Chavez
    • 3
  1. 1.Department of Electronics EngineeringUniversidad de GuanajuatoGuanajuatoMexico
  2. 2.Department of Electronics EngineeringUniversidad VeracruzanaXalapaMexico
  3. 3.Department of Electronics EngineeringUniversidad Autonoma de ZacatecasZacatecasMexico

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