Bayesian Piecewise Constant Regression of LOH and CN data (gBPCR)
SNP-microarrays are able to measure simultaneously both genotype and copy number (CN) at several Single Nucleotide Polymorphism (SNP) positions. We call LOH data the homozygous status of
the SNPs deduced from the genotyping data. Combining the two data, it is possible to better identify genomic aberrations. For example, a long sequence of homozygous SNPs might be shown due to either a uniparental disomy event (UPD), i.e. each SNP has two identical alleles both derived from only one parent, or the physical loss of one allele. In this situation, the knowledge of the copy number value can help in distinguishing between these two events.
The gBPCR algorithm is Bayesian piecewise constant regression which infers the type of aberration occurred (high amplification, gain, loss, homozygous deletion, IBD/UPD, normal state), taking into account all the possible influence in the microarray detection of the genotype, resulting from an altered copy number level.
Publications & Presentations
- Rancoita P.M.V., "Bayesian joint estimation of CN and LOH aberrations", 3rd International Workshop on Practical Applications of Computational Biology & Bioinformatics (IWPACBB'09), Salamanca, June 9-12 2009.
- Rancoita, P.M.V., Hutter, M., Bertoni, F., Kwee, I. (2009). Bayesian joint estimation of CN and LOH aberrations, in IWANN 2009, Part II, LNCS 5518, edited by S. Omatu et al., pp. 1109-1117. [link]
- Rancoita P.M.V., "Bayesian integrated genomics", Valencia 9/2010 World Meeting of the International Society for Bayesian Analysis, Benidorm June 3-8 2010.
- Rancoita, P.M.V., Hutter, M., Bertoni, F., Kwee, I. (2010). An integrated Bayesian analysis of LOH and copy number data. BMC Bioinformatics
11:321. [link]
Software
- To download the zipped folder with the source of the program and some examples, please click here
- To download the instructions and some suggestions for using the program, please click here