TY - JOUR

T1 - Jetset: selecting the optimal microarray probe set to represent a gene

A1 - Li,Qiyuan

A1 - Birkbak,Nicolai Juul

A1 - Gyorffy,Balazs

A1 - Szallasi,Zoltan Imre

A1 - Eklund,Aron Charles

AU - Li,Qiyuan

AU - Birkbak,Nicolai Juul

AU - Gyorffy,Balazs

AU - Szallasi,Zoltan Imre

AU - Eklund,Aron Charles

PB - BioMed Central Ltd.

PY - 2011

Y1 - 2011

N2 - Background: Interpretation 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. Results: We 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. Conclusions: This method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest.

AB - Background: Interpretation 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. Results: We 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. Conclusions: This method provides a simple, unambiguous mapping to allow assessment of the expression levels of specific genes of interest.

U2 - 10.1186/1471-2105-12-474

DO - 10.1186/1471-2105-12-474

JO - B M C Bioinformatics

JF - B M C Bioinformatics

SN - 1471-2105

IS - 1

VL - 12

SP - 474

ER -