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A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data

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dc.contributor.author González Ruiz, Juan Ramón
dc.contributor.author Rodríguez Santiago, Benjamín
dc.contributor.author Cáceres, Alejandro
dc.contributor.author Pique Regi, Roger
dc.contributor.author Rothman, Nathaniel
dc.contributor.author Chanock, Stephen J.
dc.contributor.author Armengol i Dulcet, Lluís
dc.contributor.author Pérez Jurado, Luis Alberto
dc.date.accessioned 2015-04-13T07:30:10Z
dc.date.available 2015-04-13T07:30:10Z
dc.date.issued 2011
dc.identifier.citation Gonzalez JR, Rodriguez-Santiago B, Caceres A, Pique-Regi R, Rothman N, Chanock SJ et al. A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data. BMC Bioinformatics. 2011;12:166. DOI: 10.1186/1471-2105-12-166
dc.identifier.issn 1471-2105
dc.identifier.uri http://hdl.handle.net/10230/23396
dc.description.abstract Background: Mosaicism for copy number and copy neutral chromosomal rearrangements has been recently identified as a relatively common source of genetic variation in the normal population. However its prevalence is poorly defined since it has been only studied systematically in one large-scale study and by using non optimal ad-hoc SNP array data analysis tools, uncovering rather large alterations (> 1 Mb) and affecting a high proportion of cells. Here we propose a novel methodology, Mosaic Alteration Detection-MAD, by providing a software tool that is effective for capturing previously described alterations as wells as new variants that are smaller in size and/or affecting a low percentage of cells. Results: The developed method identified all previously known mosaic abnormalities reported in SNP array data obtained from controls, bladder cancer and HapMap individuals. In addition MAD tool was able to detect new mosaic variants not reported before that were smaller in size and with lower percentage of cells affected. The performance of the tool was analysed by studying simulated data for different scenarios. Our method showed high sensitivity and specificity for all assessed scenarios. Conclusions: The tool presented here has the ability to identify mosaic abnormalities with high sensitivity and specificity. Our results confirm the lack of sensitivity of former methods by identifying new mosaic variants not reported in previously utilised datasets. Our work suggests that the prevalence of mosaic alterations could be higher than initially thought. The use of appropriate SNP array data analysis methods would help in defining the human genome mosaic map.
dc.description.sponsorship This work has been supported by the Spanish Ministry of Science and Innovation (MTM2008-02457 to JRG), the Fondo de Investigación Sanitaria (grant PI076832 to LAP-J), the intramural research program of the NIH, NCI (to SJC and NR) and the Asociación Española Contra el Cáncer (AECC) (to FXR and LAP-J). B. Rodríguez-Santiago was supported by a postdoctoral fellowship (FIS CD06/00019) of the Fondo Investigación Sanitaria, Spain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher BioMed Central
dc.relation.ispartof BMC Bioinformatics. 2011;12:166
dc.rights © Gonzalez JR, Rodriguez-Santiago B, Caceres A, Pique-Regi R, Rothman N, Chanock SJ, Armengol L, Perez-Jurado LA. Creative Commons Attribution License http://creativecommons.org/licenses/by/2.0/
dc.rights.uri http://creativecommons.org/licenses/by/2.0
dc.subject.other Aparell urinari
dc.subject.other Cromosomes humans -- Anomalies
dc.title A fast and accurate method to detect allelic genomic imbalances underlying mosaic rearrangements using SNP array data
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1186/1471-2105-12-166
dc.relation.projectID info:eu-repo/grantAgreement/ES/3PN/MTM2008-02457
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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