SubPatCNV (Subspace Pattern-ming of Copy Number Variations) is a data mining tool for discovery of CNV regions that exhibit in subsets of samples larger than a support threshold. SubPatCNV is suitable for analysis of arrayCGH data of a population or a patient cohort such as HapMap data or TCGA data to answer specific questions like "Which are all the chromosomal fragments showing nearly identical deletions or insertions in more than 30% of the individuals in the HapMap population or TCGA tumor samples?". SubPatCNV is the implementation of a variation of approximate association pattern mining algorithm under a spatial constraint on the positional CNV probe features. The implementation scales to high-density array data with hundreds of thousands features.

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Additional Project Details

Programming Language

C++, MATLAB

Registered

2014-04-18