Wavelet-based detection of transcriptional activity on a novel Staphylococcus aureus tiling microarray

Segura, Víctor; Toledo Arana, Alejandro; Uzqueda, Maite; Lasa Uzcudun, Íñigo; Muñoz Barrutia, Arrate

Wavelet-based detection of transcriptional activity on a novel Staphylococcus aureus tiling microarray

dc.contributor.author	Segura, Víctor
dc.contributor.author	Toledo Arana, Alejandro
dc.contributor.author	Uzqueda, Maite
dc.contributor.author	Lasa Uzcudun, Íñigo
dc.contributor.author	Muñoz Barrutia, Arrate
dc.contributor.department	IdAB. Instituto de Agrobiotecnología / Agrobioteknologiako Institutua	es_ES
dc.date.accessioned	2015-10-27T08:36:36Z
dc.date.available	2015-10-27T08:36:36Z
dc.date.issued	2012
dc.description	UPNa. Instituto de Agrobiotecnología. Laboratorio de Biofilms Microbianos	es_ES
dc.description	Incluye 7 ficheros de datos	es_ES
dc.description.abstract	Background: High-density oligonucleotide microarray is an appropriate technology for genomic analysis, and is particulary useful in the generation of transcriptional maps, ChIP-on-chip studies and re-sequencing of the genome. Transcriptome analysis of tiling microarray data facilitates the discovery of novel transcripts and the assessment of differential expression in diverse experimental conditions. Although new technologies such as next-generation sequencing have appeared, microarrays might still be useful for the study of small genomes or for the analysis of genomic regions with custom microarrays due to their lower price and good accuracy in expression quantification. Results: Here, we propose a novel wavelet-based method, named ZCL (zero-crossing lines), for the combined denoising and segmentation of tiling signals. The denoising is performed with the classical SUREshrink method and the detection of transcriptionally active regions is based on the computation of the Continuous Wavelet Transform (CWT). In particular, the detection of the transitions is implemented as the thresholding of the zero-crossing lines. The algorithm described has been applied to the public Saccharomyces cerevisiae dataset and it has been compared with two well-known algorithms: pseudo-median sliding window (PMSW) and the structural change model (SCM). As a proof-of-principle, we applied the ZCL algorithm to the analysis of the custom tiling microarray hybridization results of a S. aureus mutant deficient in the sigma B transcription factor. The challenge was to identify those transcripts whose expression decreases in the absence of sigma B. Conclusions: The proposed method archives the best performance in terms of positive predictive value (PPV) while its sensitivity is similar to the other algorithms used for the comparison. The computation time needed to process the transcriptional signals is low as compared with model-based methods and in the same range to those based on the use of filters. Automatic parameter selection has been incorporated and moreover, it can be easily adapted to a parallel implementation. We can conclude that the proposed method is well suited for the analysis of tiling signals, in which transcriptional activity is often hidden in the noise. Finally, the quantification and differential expression analysis of S. aureus dataset have demonstrated the valuable utility of this novel device to the biological analysis of the S. aureus transcriptome.	en
dc.description.sponsorship	This work was supported by the Spanish Torres-Quevedo fellowship [PTQ-08-03-07769] to VS. ATA and AMB were supported by Spanish Ministry of Science and Innovation ‘Ramón y Cajal’ contracts. This work was supported by the Spanish Ministry of Science and Innovation Grants BIO2008-05284-C02-01, BFU2011-23222, ERA-NET Pathogenomics PIM2010EPA-00606 and the agreement between ‘Fundación para la Investigación médica aplicada’ (FIMA) and the ’UTE project CIMA’.	en
dc.format.mimetype	application/pdf	en
dc.format.mimetype	application/zip	en
dc.identifier.doi	10.1186/1471-2105-13-222
dc.identifier.issn	1471-2105
dc.identifier.uri	https://academica-e.unavarra.es/handle/2454/18634
dc.language.iso	eng	en
dc.publisher	BioMed Central	en
dc.relation.ispartof	BMC Bioinformatics 2012, 13:222	en
dc.relation.projectID	info:eu-repo/grantAgreement/MICINN//BIO2008-05284-C02-01/ES/
dc.relation.projectID	info:eu-repo/grantAgreement/ES/6PN/BFU2011-23222/
dc.relation.publisherversion	https://dx.doi.org/10.1186/1471-2105-13-222
dc.rights	© 2012 Segura et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.	en
dc.rights.accessRights	info:eu-repo/semantics/openAccess
dc.rights.uri	http://creativecommons.org/licenses/by/2.0/
dc.rights.uri	http://creativecommons.org/publicdomain/zero/1.0/
dc.subject	Array data	en
dc.subject	Chip-chip	en
dc.subject	Genome	en
dc.subject	Sigma(b)	en
dc.subject	Landscape	en
dc.subject	Shrinkage	en
dc.subject	Virulence	en
dc.subject	Model	en
dc.subject	Sara	en
dc.subject	RNAS	en
dc.title	Wavelet-based detection of transcriptional activity on a novel Staphylococcus aureus tiling microarray	en
dc.type	info:eu-repo/semantics/article
dc.type.version	info:eu-repo/semantics/publishedVersion
dspace.entity.type	Publication
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