Dataset Information

Automated design of paralogue ratio test assays for the accurate and rapid typing of copy number variation.

ABSTRACT:

Motivation

Genomic copy number variation (CNV) can influence susceptibility to common diseases. High-throughput measurement of gene copy number on large numbers of samples is a challenging, yet critical, stage in confirming observations from sequencing or array Comparative Genome Hybridization (CGH). The paralogue ratio test (PRT) is a simple, cost-effective method of accurately determining copy number by quantifying the amplification ratio between a target and reference amplicon. PRT has been successfully applied to several studies analyzing common CNV. However, its use has not been widespread because of difficulties in assay design.

Results

We present PRTPrimer (www.prtprimer.org) software for automated PRT assay design. In addition to stand-alone software, the web site includes a database of pre-designed assays for the human genome at an average spacing of 6 kb and a web interface for custom assay design. Other reference genomes can also be analyzed through local installation of the software. The usefulness of PRTPrimer was tested within known CNV, and showed reproducible quantification. This software and database provide assays that can rapidly genotype CNV, cost-effectively, on a large number of samples and will enable the widespread adoption of PRT.

Availability

PRTPrimer is available in two forms: a Perl script (version 5.14 and higher) that can be run from the command line on Linux systems and as a service on the PRTPrimer web site (www.prtprimer.org).

SUBMITTER: Veal CD

PROVIDER: S-EPMC3722521 | biostudies-literature | 2013 Aug

REPOSITORIES: biostudies-literature

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Publications

Automated design of paralogue ratio test assays for the accurate and rapid typing of copy number variation.

Veal Colin D CD Xu Hang H Reekie Katherine K Free Robert R Hardwick Robert J RJ McVey David D Brookes Anthony J AJ Hollox Edward J EJ Talbot Christopher J CJ

Bioinformatics (Oxford, England) 20130606 16

<h4>Motivation</h4>Genomic copy number variation (CNV) can influence susceptibility to common diseases. High-throughput measurement of gene copy number on large numbers of samples is a challenging, yet critical, stage in confirming observations from sequencing or array Comparative Genome Hybridization (CGH). The paralogue ratio test (PRT) is a simple, cost-effective method of accurately determining copy number by quantifying the amplification ratio between a target and reference amplicon. PRT ha ...[more]

PMID: 23742985

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Project description:Copy number variants (CNVs) are the gain or loss of DNA segments in the genome. Studies have shown that CNVs are linked to various disorders, including autism, intellectual disability, and schizophrenia. Consequently, the interest in studying a possible association of CNVs to specific disease traits is growing. However, due to the specific multi-dimensional characteristics of the CNVs, methods for testing the association between CNVs and the disease-related traits are still underdeveloped. We propose a novel multi-dimensional CNV kernel association test (MCKAT) in this paper. We aim to find significant associations between CNVs and disease-related traits using kernel-based methods. We address the multi-dimensionality in CNV characteristics. We first design a single pair CNV kernel, which contains three sub-kernels to summarize the similarity between two CNVs considering all CNV characteristics. Then, aggregate single pair CNV kernel to the whole chromosome CNV kernel, which summarizes the similarity between CNVs in two or more chromosomes. Finally, the association between the CNVs and disease-related traits is evaluated by comparing the similarity in the trait with kernel-based similarity using a score test in a random effect model. We apply MCKAT on genome-wide CNV datasets to examine the association between CNVs and disease-related traits, which demonstrates the potential usefulness the proposed method has for the CNV association tests. We compare the performance of MCKAT with CKAT, a uni-dimensional kernel method. Based on the results, MCKAT indicates stronger evidence, smaller p-value, in detecting significant associations between CNVs and disease-related traits in both rare and common CNV datasets. A multi-dimensional copy number variant kernel association test can detect statistically significant associated CNV regions with any disease-related trait. MCKAT can provide biologists with CNV hot spots at the cytogenetic band level that CNVs on them may have a significant association with disease-related traits. Using MCKAT, biologists can narrow their investigation from the whole genome, including many genes and CNVs, to more specific cytogenetic bands that MCKAT identifies. Furthermore, MCKAT can help biologists detect significantly associated CNVs with disease-related traits across a patient group instead of examining each subject's CNVs case by case.

Dataset Information

Automated design of paralogue ratio test assays for the accurate and rapid typing of copy number variation.

Motivation

Results

Availability

Publications

Automated design of paralogue ratio test assays for the accurate and rapid typing of copy number variation.

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