The Experts below are selected from a list of 440775 Experts worldwide ranked by ideXlab platform
Ursula R. Kees - One of the best experts on this subject based on the ideXlab platform.
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Gene expression levels assessed by oligonucleotide Microarray analysis and quantitative real-time RT-PCR - How well do they correlate?
BMC Genomics, 2005Co-Authors: Peter B. Dallas, Nicholas G. Gottardo, Martin J. Firth, Philippa A. Terry, Joseph R. Freitas, Joanne M. Boag, Aaron J. Cummings, Katrin Hoffmann, Alex H. Beesley, Ursula R. KeesAbstract:The use of Microarray technology to assess gene expression levels is now widespread in biology. The validation of Microarray results using independent mRNA quantitation techniques remains a desirable element of any Microarray experiment. To facilitate the comparison of Microarray expression data between laboratories it is essential that validation methodologies be critically examined. We have assessed the correlation between expression scores obtained for 48 human genes using oligonucleotide Microarrays and the expression levels for the same genes measured by quantitative real-time RT-PCR (qRT-PCR).
Raymond R Samaha - One of the best experts on this subject based on the ideXlab platform.
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large scale real time pcr validation on gene expression measurements from two commercial long oligonucleotide Microarrays
BMC Genomics, 2006Co-Authors: Yulei Wang, Catalin Barbacioru, Fiona Hyland, Wenming Xiao, Kathryn Hunkapiller, Julie Blake, Frances Chan, Carolyn Gonzalez, Lu Zhang, Raymond R SamahaAbstract:DNA Microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the Microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various Microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial Microarray platforms. In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide Microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both Microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two Microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan® Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different Microarray platforms. We conclude that Microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of Microarrays; understanding these limitations will enable researchers to more effectively evaluate Microarray results in a more cautious and appropriate manner.
Yulei Wang - One of the best experts on this subject based on the ideXlab platform.
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long versus short oligonucleotide Microarrays for the study of gene expression in nonhuman primates
Journal of Neuroscience Methods, 2006Co-Authors: Stephen J Walker, Yulei Wang, Frances Chan, Kathleen A Grant, Gary M HellmannAbstract:Abstract The high degree of sequence similarity between human and nonhuman primate (NHP) genomic DNA suggests that human genome sequence-based DNA Microarrays may be used effectively to study gene expression in NHP disease models. In the present study, two distinct commercially available human genome Microarray platforms, the Affymetrix HG U133A GeneChip ® System utilizing Human Genome U133A GeneChips ® and the Applied Biosystems Expression Array System utilizing the Human Genome Survey Microarray, were used to identify and characterize gene expression changes in the anterior cerebellum of a macaque monkey model of human alcoholism. The Affymetrix Microarray consists of eleven short oligonucleotide probe sets for each gene while the Applied Biosystems Microarray uses a single long oligonucleotide per gene. Cross-mapping of probes revealed a total of 11,542 genes that are represented on both Microarray platforms. Absolute measures of gene expression (“present calls”) from the cerebellum RNA samples were 65–70% (Applied Biosystems Expression Array System) and 27–30% (AffymetrixGeneChip ® System) among these common gene targets. Analysis of variance (ANOVA; p 1.2 fold change; detected on at least 50% of the arrays) indicated 932 and 515 differentially expressed genes for the Applied Biosystems and Affymetrix Microarrays, respectively. Significance analysis of Microarrays (SAM) identified 255 significant genes at 5% false discovery rate (FDR) for the Applied Biosystems data set and five significant genes at 60% FDR (minimum FDR) for the Affymetrix data set. TaqMan ® assay-based real-time PCR validation of a number of differentially-expressed genes yielded results that agreed well with the array data in the majority of comparisons. This study demonstrates that human sequence-based DNA arrays can be used effectively to detect differential gene expression in an NHP disease model and provides evidence that the use of this long oligonucleotide-based Microarray platform may be more suitable for cross-species gene expression studies than a short oligonucleotide-based system.
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large scale real time pcr validation on gene expression measurements from two commercial long oligonucleotide Microarrays
BMC Genomics, 2006Co-Authors: Yulei Wang, Catalin Barbacioru, Fiona Hyland, Wenming Xiao, Kathryn Hunkapiller, Julie Blake, Frances Chan, Carolyn Gonzalez, Lu Zhang, Raymond R SamahaAbstract:DNA Microarrays are rapidly becoming a fundamental tool in discovery-based genomic and biomedical research. However, the reliability of the Microarray results is being challenged due to the existence of different technologies and non-standard methods of data analysis and interpretation. In the absence of a "gold standard"/"reference method" for the gene expression measurements, studies evaluating and comparing the performance of various Microarray platforms have often yielded subjective and conflicting conclusions. To address this issue we have conducted a large scale TaqMan® Gene Expression Assay based real-time PCR experiment and used this data set as the reference to evaluate the performance of two representative commercial Microarray platforms. In this study, we analyzed the gene expression profiles of three human tissues: brain, lung, liver and one universal human reference sample (UHR) using two representative commercial long-oligonucleotide Microarray platforms: (1) Applied Biosystems Human Genome Survey Microarrays (based on single-color detection); (2) Agilent Whole Human Genome Oligo Microarrays (based on two-color detection). 1,375 genes represented by both Microarray platforms and spanning a wide dynamic range in gene expression levels, were selected for TaqMan® Gene Expression Assay based real-time PCR validation. For each platform, four technical replicates were performed on the same total RNA samples according to each manufacturer's standard protocols. For Agilent arrays, comparative hybridization was performed using incorporation of Cy5 for brain/lung/liver RNA and Cy3 for UHR RNA (common reference). Using the TaqMan® Gene Expression Assay based real-time PCR data set as the reference set, the performance of the two Microarray platforms was evaluated focusing on the following criteria: (1) Sensitivity and accuracy in detection of expression; (2) Fold change correlation with real-time PCR data in pair-wise tissues as well as in gene expression profiles determined across all tissues; (3) Sensitivity and accuracy in detection of differential expression. Our study provides one of the largest "reference" data set of gene expression measurements using TaqMan® Gene Expression Assay based real-time PCR technology. This data set allowed us to use an alternative gene expression technology to evaluate the performance of different Microarray platforms. We conclude that Microarrays are indeed invaluable discovery tools with acceptable reliability for genome-wide gene expression screening, though validation of putative changes in gene expression remains advisable. Our study also characterizes the limitations of Microarrays; understanding these limitations will enable researchers to more effectively evaluate Microarray results in a more cautious and appropriate manner.
Sabine Bahn - One of the best experts on this subject based on the ideXlab platform.
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Quantitative polymerase chain reaction: Validation of Microarray results from postmortem brain studies
Biological Psychiatry, 2004Co-Authors: Michael Mimmack, Justin Brooking, Sabine BahnAbstract:Quantitative polymerase chain reaction (Q-PCR) is now considered the "technique of choice" for validating gene expression changes identified with ribonucleic acid-based expression profiling technologies (especially micro- and macroarray techniques). The identification of altered gene expression profiles with Microarrays is best viewed as the first step in the determination of potential disease-associated genes; however, the false-positive rate can be high, particularly with small sample sets and in view of the typically small differences observed in brain expression studies. Quantitative PCR is a rapid and highly sensitive technique for accurate quantification of Microarray results; however, careful consideration of experimental design, quality of primer/probe design, internal standards, and normalization procedures are pivotal, particularly when the work involves postmortem tissue.
Peter B. Dallas - One of the best experts on this subject based on the ideXlab platform.
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Gene expression levels assessed by oligonucleotide Microarray analysis and quantitative real-time RT-PCR - How well do they correlate?
BMC Genomics, 2005Co-Authors: Peter B. Dallas, Nicholas G. Gottardo, Martin J. Firth, Philippa A. Terry, Joseph R. Freitas, Joanne M. Boag, Aaron J. Cummings, Katrin Hoffmann, Alex H. Beesley, Ursula R. KeesAbstract:The use of Microarray technology to assess gene expression levels is now widespread in biology. The validation of Microarray results using independent mRNA quantitation techniques remains a desirable element of any Microarray experiment. To facilitate the comparison of Microarray expression data between laboratories it is essential that validation methodologies be critically examined. We have assessed the correlation between expression scores obtained for 48 human genes using oligonucleotide Microarrays and the expression levels for the same genes measured by quantitative real-time RT-PCR (qRT-PCR).
