Using the arrayCGH framework developped in the package GLAD, which is available under Bioconductor. We propose the formalism of flags to handle clone and spot filtering: the core of the normalization process consists in applying to an arrayCGH object a list of flags that successively exclude from the data all irrelevant spots or clones.
We also define quality scores (qscores) allowing to evaluate the quality of an array after normalization: these scores can be used directly to compare the quality of different arrays after the same normalization process, or to compare the efficiency of different normalization processes on a given array or on a given batch of arrays.
This document is organized as follows: after a short description of optional items we add to arrayCGH objects (section 2, we introduce the classes flag (section 3) and qscore (section 4) with their attributes and dedicated methods; then we describe two useful graphical representation functions (section 6), namely genome.plot and report.plot; Afterwards we give a short description of the array-CGH datasets we provide (section 5); finally we illustrate the usage of MANOR by a sample R script (section 7).
Pierre Neuvial 2007-03-16