Jetset: selecting the optimal microarray probe set to represent a gene

BMC Bioinformatics

Methodology Article

Nicolai J Birkbak¹  Aron C Eklund¹  Qiyuan Li¹  Zoltan Szallasi²  Balazs Gyorffy³ 

[1] Center for Biological Sequence Analysis, Technical University of Denmark, 2800, Lyngby, Denmark;Center for Biological Sequence Analysis, Technical University of Denmark, 2800, Lyngby, Denmark;Children's Hospital Informatics Program at the Harvard-MIT Division of Health Sciences and Technology (CHIP@HST), Harvard Medical School, 02115, Boston, MA, USA;Semmelweis University 1st Dept of Pediatrics, Joint Research Laboratory of the Hungarian Academy of Sciences and the Semmelweis University, H-1083, Budapest, Hungary;

关键词: Splice Isoforms;    ESR1 Gene;    Coverage Score;    Robustness Score;    CIN70 Gene;   

DOI  :  10.1186/1471-2105-12-474

 received in 2011-09-12, accepted in 2011-12-15,  发布年份 2011

来源: Springer

【 摘 要 】

BackgroundInterpretation of gene expression microarrays requires a mapping from probe set to gene. On many Affymetrix gene expression microarrays, a given gene may be detected by multiple probe sets, which may deliver inconsistent or even contradictory measurements. Therefore, obtaining an unambiguous expression estimate of a pre-specified gene can be a nontrivial but essential task.ResultsWe developed scoring methods to assess each probe set for specificity, splice isoform coverage, and robustness against transcript degradation. We used these scores to select a single representative probe set for each gene, thus creating a simple one-to-one mapping between gene and probe set. To test this method, we evaluated concordance between protein measurements and gene expression values, and between sets of genes whose expression is known to be correlated. For both test cases, we identified genes that were nominally detected by multiple probe sets, and we found that the probe set chosen by our method showed stronger concordance.ConclusionsThis method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest.

【 授权许可】

Unknown   
© Li et al; licensee BioMed Central Ltd. 2011. This article is published under license to 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.