dc.contributor.author | Rueda, Oscar M. | |
dc.contributor.author | Díaz Uriarte, Ramón | |
dc.contributor.other | UAM. Departamento de Bioquímica | es_ES |
dc.date.accessioned | 2016-02-24T13:13:17Z | |
dc.date.available | 2016-02-24T13:13:17Z | |
dc.date.issued | 2007-10-16 | |
dc.identifier.citation | BMC Bioinformatics 8 (2007): 394 | en_US |
dc.identifier.issn | 1471-2105 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10486/669894 | |
dc.description.abstract | Background: Yu et al. (BMC Bioinformatics 2007,8: 145+) have recently compared the
performance of several methods for the detection of genomic amplification and deletion
breakpoints using data from high-density single nucleotide polymorphism arrays. One of the
methods compared is our non-homogenous Hidden Markov Model approach. Our approach uses
Markov Chain Monte Carlo for inference, but Yu et al. ran the sampler for a severely insufficient
number of iterations for a Markov Chain Monte Carlo-based method. Moreover, they did not use
the appropriate reference level for the non-altered state.
Methods: We rerun the analysis in Yu et al. using appropriate settings for both the Markov Chain
Monte Carlo iterations and the reference level. Additionally, to show how easy it is to obtain
answers to additional specific questions, we have added a new analysis targeted specifically to the
detection of breakpoints.
Results: The reanalysis shows that the performance of our method is comparable to that of the
other methods analyzed. In addition, we can provide probabilities of a given spot being a
breakpoint, something unique among the methods examined.
Conclusion: Markov Chain Monte Carlo methods require using a sufficient number of iterations
before they can be assumed to yield samples from the distribution of interest. Running our method
with too small a number of iterations cannot be representative of its performance. Moreover, our
analysis shows how our original approach can be easily adapted to answer specific additional
questions (e.g., identify edges) | en_US |
dc.description.sponsorship | Funding provided by Fundacion de Investigacion Medica Mutua Madrilena.
R.D.-U. is partially supported by the Ramon y Cajal programme of the Spanish
MEC | en_US |
dc.format.extent | 9 pag. | es_ES |
dc.format.mimetype | application/pdf | en |
dc.language.iso | eng | en |
dc.publisher | BioMed Central | en_US |
dc.relation.ispartof | BMC Bioinformatics | en_US |
dc.rights | © 2007 Rueda and Diaz-Uriarte; licensee BioMed Central Ltd. | es_ES |
dc.subject.other | Chromosome Breakage | en_US |
dc.subject.other | Gene Deletion | en_US |
dc.subject.other | Genome, Human | en_US |
dc.subject.other | Markov Chains | en_US |
dc.subject.other | Monte Carlo Method | en_US |
dc.title | A response to Yu et al. "A forward-backward fragment assembling algorithm for the identification of genomic amplification and deletion breakpoints using high-density single nucleotide polymorphism (SNP) array", BMC Bioinformatics 2007, 8: 145 | en_US |
dc.type | article | en |
dc.subject.eciencia | Biología y Biomedicina / Biología | es_ES |
dc.relation.publisherversion | http://www.biomedcentral.com/1471-2105/8/394 | es_ES |
dc.identifier.doi | 10.1186/1471-2105-8-394 | es_ES |
dc.identifier.publicationfirstpage | 394-1 | es_ES |
dc.identifier.publicationlastpage | 394-9 | es_ES |
dc.identifier.publicationvolume | 8 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | en |
dc.rights.cc | Reconocimiento | es_ES |
dc.rights.accessRights | openAccess | en |
dc.facultadUAM | Facultad de Medicina | |