Cancer Informatics (Jan 2007)

Normalized, Segmented or Called aCGH Data?

  • Bauke Ylstra,
  • Mark A. van de Wiel,
  • Wessel N. van Wieringen

Journal volume & issue
Vol. 3
pp. 321 – 327

Abstract

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Array comparative genomic hybridization (aCGH) is a high-throughput lab technique to measure genome-wide chromosomal copy numbers. Data from aCGH experiments require extensive pre-processing, which consists of three steps: normalization, segmentation and calling. Each of these pre-processing steps yields a different data set: normalized data, segmented data, and called data. Publications using aCGH base their fi ndings on data from all stages of the pre-processing. Hence, there is no consensus on which should be used for further down-stream analysis. This consensus is however important for correct reporting of findings, and comparison of results from different studies. We discuss several issues that should be taken into account when deciding on which data are to be used. We express the believe that called data are best used, but would welcome opposing views.

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