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BMC Genomics ; 14: 367, 2013 May 31.
Artigo em Inglês | MEDLINE | ID: mdl-23724825

RESUMO

BACKGROUND: Mosaic somatic alterations are present in all multi-cellular organisms, but the physiological effects of low-level mosaicism are largely unknown. Most mosaic alterations remain undetectable with current analytical approaches, although the presence of such alterations is increasingly implicated as causative for disease. RESULTS: Here, we present the Parent-of-Origin-based Detection (POD) method for chromosomal abnormality detection in trio-based SNP microarray data. Our software implementation, triPOD, was benchmarked using a simulated dataset, outperformed comparable software for sensitivity of abnormality detection, and displayed substantial improvement in the detection of low-level mosaicism while maintaining comparable specificity. Examples of low-level mosaic abnormalities from a large autism dataset demonstrate the benefits of the increased sensitivity provided by triPOD. The triPOD analyses showed robustness across multiple types of Illumina microarray chips. Two large, clinically-relevant datasets were characterized and compared. CONCLUSIONS: Our method and software provide a significant advancement in the ability to detect low-level mosaic abnormalities, thereby opening new avenues for research into the implications of mosaicism in pathogenic and non-pathogenic processes.


Assuntos
Aberrações Cromossômicas , Biologia Computacional/métodos , Algoritmos , Internet , Análise de Sequência com Séries de Oligonucleotídeos , Polimorfismo de Nucleotídeo Único , Software
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