La méthode (gBPCR) pour estimer à la fois les aberrations LOH et CN

Background

Cancer and other disorders are due to genomic lesions. SNP-microarrays are able to measure simultaneously both genotype and copy number (CN) at several Single Nucleotide Polymorphisms (SNPs) along the genome. CN is defined as the number of DNA copies, and the normal is two, since we have two copies of each chromosome. The genotype of a SNP is the status given by the nucleotides (alleles) which are present on the two copies of DNA. It is defined homozygous or heterozygous if the two alleles are the same or if they differ, respectively. Loss of heterozygosity (LOH) is the loss of the heterozygous status due to genomic events.

Combining CN and LOH data, it is possible to better identify different types of genomic aberrations. For example, a long sequence of homozygous SNPs might be caused by either the physical loss of one copy or a uniparental disomy event (UPD), i.e. each SNP has two identical nucleotides both derived from only one parent. In this situation, the knowledge of the CN can help in distinguishing between these two events.

Results

To better identify genomic aberrations, we propose a method (called gBPCR) which infers the type of aberration occurred, taking into ACCOUNT all the possible influence in the microarray detection of the homozygosity status of the SNPs, resulting from an altered CN level. Namely, we model the distributions of the detected genotype, given a specific genomic alteration and we estimate the parameters involved on public reference datasets. The estimation is performed similarly to the modified Bayesian Piecewise Constant Regression, but with improved estimators for the detection of the breakpoints.

Using artificial and real data, we evaluate the quality of the estimation of gBPCR and we also show that it outperforms other well-known methods for LOH estimation.

Conclusions

We propose a method (gBPCR) for the estimation of both LOH and CN aberrations, improving their estimation by integrating both types of data and ACCOUNTING for their relationships. Moreover, gBPCR performed very well in comparison with other methods for LOH estimation and the estimated CN lesions on real data have been validated with another technique.

Background

Although most of the human genome is identical among individuals, there are about 10 million single nucleotide polymorphisms (SNPs) which distinguish us [1]. SNPs are single base-pair loci where the nucleotides can assume two possible values (called alleles) among the four bases (thymine, adenine, cytosine, guanine). In general, since we have two copies of each chromosome, the genotype at any SNP can be: AA, BB or AB, where A and B represent the two alleles. Moreover, a SNP can be classified as homozygous (i.e., AA or BB) or heterozygous (i.e., AB), whether or not its genotype consists of two equal alleles. Cancer and several human diseases are caused by genomic aberrations, which can affect the homozygous status and/or the DNA copy number (the normal copy number, CN, is two since we have two copies of each chromosome, except for the chromosomes X and Y). The former type of aberrations is often displayed by unusual long stretches of homozygous SNPs, called loss of heterozygosity (LOH) region. The latter type of aberrations consists in genomic

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