TY - JOUR
T1 - Enhanced identification and biological validation of differential gene expression via Illumina whole-genome expression arrays through the use of the model-based background correction methodology
AU - Ding, Liang Hao
AU - Xie, Yang
AU - Park, Seongmi
AU - Xiao, Guanghua
AU - Story, Michael D.
N1 - Funding Information:
We would like to thank Shane Scoggin of the Simmons Cancer Center Genomics Core, UT Southwestern Medical Center, for processing all samples for microarray analysis. This study was funded by grants from NASA NSCORS NAG9-1569, NNJ05HD36G, NCI CA06294 and NIH UL1RR024982. Funding to pay the Open Access publication charges for this article was provided by NASA.
PY - 2008/6
Y1 - 2008/6
N2 - Despite the tremendous growth of microarray usage in scientific studies, there is a lack of standards for background correction methodologies, especially in single-color microarray platforms. Traditional background subtraction methods often generate negative signals and thus cause large amounts of data loss. Hence, some researchers prefer to avoid background corrections, which typically result in the underestimation of differential expression. Here, by utilizing nonspecific negative control features integrated into Illumina whole genome expression arrays, we have developed a method of model-based background correction for BeadArrays (MBCB). We compared the MBCB with a method adapted from the Affymetrix robust multi-array analysis algorithm and with no background subtraction, using a mouse acute myeloid leukemia (AML) dataset. We demonstrated that differential expression ratios obtained by using the MBCB had the best correlation with quantitative RT-PCR. MBCB also achieved better sensitivity in detecting differentially expressed genes with biological significance. For example, we demonstrated that the differential regulation of Tnfr2, Ikk and NF-kappaB, the death receptor pathway, in the AML samples, could only be detected by using data after MBCB implementation. We conclude that MBCB is a robust background correction method that will lead to more precise determination of gene expression and better biological interpretation of Illumina BeadArray data.
AB - Despite the tremendous growth of microarray usage in scientific studies, there is a lack of standards for background correction methodologies, especially in single-color microarray platforms. Traditional background subtraction methods often generate negative signals and thus cause large amounts of data loss. Hence, some researchers prefer to avoid background corrections, which typically result in the underestimation of differential expression. Here, by utilizing nonspecific negative control features integrated into Illumina whole genome expression arrays, we have developed a method of model-based background correction for BeadArrays (MBCB). We compared the MBCB with a method adapted from the Affymetrix robust multi-array analysis algorithm and with no background subtraction, using a mouse acute myeloid leukemia (AML) dataset. We demonstrated that differential expression ratios obtained by using the MBCB had the best correlation with quantitative RT-PCR. MBCB also achieved better sensitivity in detecting differentially expressed genes with biological significance. For example, we demonstrated that the differential regulation of Tnfr2, Ikk and NF-kappaB, the death receptor pathway, in the AML samples, could only be detected by using data after MBCB implementation. We conclude that MBCB is a robust background correction method that will lead to more precise determination of gene expression and better biological interpretation of Illumina BeadArray data.
UR - http://www.scopus.com/inward/record.url?scp=45549109664&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=45549109664&partnerID=8YFLogxK
U2 - 10.1093/nar/gkn234
DO - 10.1093/nar/gkn234
M3 - Article
C2 - 18450815
AN - SCOPUS:45549109664
SN - 0305-1048
VL - 36
JO - Nucleic acids research
JF - Nucleic acids research
IS - 10
M1 - e58
ER -