CDCOCA: a statistical method to define complexity dependent co-occurring chromosomal aberrations
© Kumar et al; licensee BioMed Central Ltd. 2010
Published: 11 October 2010
Copy number alterations (CNA) play a key role in cancer development and progression. In general, more than one CNA can be detected in any given tumor; therefore co-occurring genetic CNA may point to co-operating cancer related genes. Existing methods for co-occurrence evaluation so far have not considered the overall heterogeneity of CNAs per tumor, resulting in a preferential detection of frequent changes with limited specificity for each association owing to the frequently high genetic instability of the samples.
Our CDCOCA algorithm has constitutes a new approach to establish statistically significant co-occurring regional genomic imbalances from for example CGH data sets containing at least hundreds of individual copy number profiles. Along with finding CNAs from low/intermediate complexity samples, our algorithm points towards a generally low statistical specificity for co-occurrence of regional CNAs in a CNA rich samples, with a negative impact on pathway modeling approaches based on genomic copy number screening analyses derived from such data.
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