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A free software tool for copy number variation (CNV) detection from SNP genotyping arrays. PennCNV can handle signal intensity data from Illumina and Affymetrix arrays. With appropriate preparation of file format, it can also handle other types of SNP arrays and oligonucleotide arrays. PennCNV implements a hidden Markov model (HMM) that integrates multiple sources of information to infer CNV calls for individual genotyped samples. It differs from segmentation-based algorithm in that it considered SNP allelic ratio distribution as well as other factors, in addition to signal intensity alone. In addition, PennCNV can optionally utilize family information to generate family-based CNV calls by several different algorithms. Furthermore, PennCNV can generate CNV calls given a specific set of candidate CNV regions, through a validation-calling algorithm.


Provides a practical solution to a problem that is recognized by many researchers working with CGH arrays. NoWaves removes the wave bias from tumor profiles, thereby allowing for more accurate breakpoint detection in those profiles. We show that our algorithm, based on ridge regression, has several advantages: (i) it is robust against error-in-variables due to measurement noise in the covariates; (ii) the ridge penalty stabilizes the regression model in the presence of collinearity between the covariates; (iii) it is robust against the presence of CNAs in tumors.