Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project

Patterson, Tucker A.; Lobenhofer, Edward K.; Fulmer-Smentek, Stephanie; Collins, Patrick J.; Chu, Tzu‐Ming; Bao, Wenjun; Fang, Hong; Kawasaki, Ernest S.; Hager, Janet; Tikhonova, Irina; Walker, Stephen J.; Zhang, Liang; Hurban, Patrick; Longueville, Françoise de; Fuscoe, James C.; Tong, Weida; Shi, Leming; Wolfinger, Russell D.

doi:10.1038/nbt1242

Cited by 429 publications

(308 citation statements)

References 23 publications

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“…to different sets of candidate biomarkers [2,3]. In addition to all of these technical obstacles, the practical limitation of finding datasets which measure the same scientific question further hampers data combination.…”

Section: Introductionmentioning

confidence: 99%

Combining multiple microarray studies using bootstrap meta-analysis

Barrett

Phan

Wang

2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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Microarray technology has enabled us to simultaneously measure the expression of thousands of genes. Using this high-throughput technology, we can examine subtle genetic changes between biological samples and build predictive models for clinical applications. Although microarrays have dramatically increased the rate of data collection, sample size is still a major issue when selecting features. Previous methods show that combining multiple microarray datasets improves feature selection using simple methods such as fold change. We propose a wrapper-based gene selection technique that combines bootstrap estimated classification errors for individual genes across multiple datasets and reduces the contribution of datasets with high variance. We use the bootstrap because it is an unbiased estimator of classification error that is also effective for small sample data. Coupled with data combination across multiple datasets, we show that our metaanalytic approach improves the biological relevance of gene selection using prostate and renal cancer microarray data.

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Section: Introductionmentioning

confidence: 99%

Combining multiple microarray studies using bootstrap meta-analysis

Barrett

Phan

Wang

2008

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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“…However, affected tissues are not always easily accessible, as is the case in neurodegenerative diseases [7]. establishing that these effects are also mirrored in blood [27]. Furthermore, assessing the blood cell count of patients, exclusion of patients with infection and keeping track of therapy the patient is receiving will also reduce the bias which can influence the final results of the studies.…”

Section: Novel Genomic Approaches In Predictive Medicinementioning

confidence: 99%

Quest for new genomic and proteomic biomarkers in neurology

Gotovac

Pivac

Hajnšek

et al. 2011

Translational Neuroscience

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The possibility of identifying novel biomarkers for neurodegenerative diseases has been greatly enhanced with recent advances in genomics and proteomics. Novel technologies have the potential to hasten the development of new biomarkers useful as predictors of disease etiology and outcome, as well as responsiveness to therapy. Disease-modifying new therapies are very much needed in modern approaches to treatment of neurodegenerative diseases. Current progress in the field encounters a degree of skepticism about the reliability of genomic and proteomic data and its relevance for clinical applications. Standard operating procedures covering sample collection, methodology and statistical analysis need to be fully developed and strictly adhered to in order to assure reproducible and clinically relevant results. Previous studies involving patients with neurodegenerative diseases show promise in using genomic and proteomic approaches for development of new biomarkers. Confirmation of any novel biomarker in multiple independent patient cohorts and correlation of the improvement in biomarker endpoint with clinical improvement in longitudinal patient studies remains crucial for future successful application. We propose that a combination of approaches in biomarker discovery may in the end lead to identification of promising candidates at DNA, RNA, protein and small molecule level.

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“…Gene profiling of the myocardial ischemic regions from I/R group and control group were carried out according to the manufacturer's instructions [40][41][42]. …”

Section: Gene Expression Microarraymentioning

confidence: 99%

Altered myocardial gene expression profiling in the ischemic tissues at different time points after cardiac ischemia/reperfusion in rats

Li¹,

Lin²,

He³

et al. 2018

Oncotarget

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We used Agilent Gene Expression microarray to analyze differential gene and lncRNA expression patterns in the myocardial ischemia regions during ischemia/ reperfusion (I/R)-induced cardiac injury in rats. Male SD rats were assigned into control group, 2 h group (30 min ischemia followed by 2 h reperfusion), 0.5 h (30 min ischemia followed by 0.5h reperfusion) group. We observed that of 18090 lncRNAs, an average of 233 lncRNAs was up-regulated in ischemic tissues of 2 h group, compared with those in control group, while an average of 6115 lncRNAs was down-regulated (with a > 2.0 fold-change and p < 0.05). Further, a total of 3135 mRNAs were differentially expressed between control group and 2h group, in which 542 mRNAs were up-regulated and 2593 mRNAs were down-regulated. Some differentially expressed genes were validated by qRT-PCR analyses of select lncRNAs in different time points after cardiac I/R injury. We unveiled that the expressions of lncRNA XR_345533.2, NONRATT025386, NONRATT024318, XR_599241.1, and NONRATT025509 were significantly up-regulated in 2h group compared with control group and 0.5h group, whereas the expression of lncRNA NR_130708.1 was downregulated after cardiac I/R injury and had no statistically different between 0.5h group and 2h group. Otherwise, the expressions of lncRNA NONRATT028627, NONRATT021959, XR_590005.1 and NONRATT023191 were significantly up-regulated in 2h group compared with 0.5h group. These findings provide evidence for differential expression patterns of mRNAs and lncRNAs in the ischemic tissues after cardiac I/R injury in rats.

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Performance comparison of one-color and two-color platforms within the Microarray Quality Control (MAQC) project

Cited by 429 publications

References 23 publications

Combining multiple microarray studies using bootstrap meta-analysis

Combining multiple microarray studies using bootstrap meta-analysis

Quest for new genomic and proteomic biomarkers in neurology

Altered myocardial gene expression profiling in the ischemic tissues at different time points after cardiac ischemia/reperfusion in rats

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