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Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization

Overview of attention for article published in BMC Genomics, May 2014
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Title
Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization
Published in
BMC Genomics, May 2014
DOI 10.1186/1471-2164-15-379
Pubmed ID
Authors

Andy Forreryd, Henrik Johansson, Ann-Sofie Albrekt, Malin Lindstedt

Abstract

Allergic contact dermatitis (ACD) develops upon exposure to certain chemical compounds termed skin sensitizers. To reduce the occurrence of skin sensitizers, chemicals are regularly screened for their capacity to induce sensitization. The recently developed Genomic Allergen Rapid Detection (GARD) assay is an in vitro alternative to animal testing for identification of skin sensitizers, classifying chemicals by evaluating transcriptional levels of a genomic biomarker signature. During assay development and biomarker identification, genome-wide expression analysis was applied using microarrays covering approximately 30,000 transcripts. However, the microarray platform suffers from drawbacks in terms of low sample throughput, high cost per sample and time consuming protocols and is a limiting factor for adaption of GARD into a routine assay for screening of potential sensitizers. With the purpose to simplify assay procedures, improve technical parameters and increase sample throughput, we assessed the performance of three high throughput gene expression platforms--nCounter®, BioMark HD™ and OpenArray®--and correlated their performance metrics against our previously generated microarray data. We measured the levels of 30 transcripts from the GARD biomarker signature across 48 samples. Detection sensitivity, reproducibility, correlations and overall structure of gene expression measurements were compared across platforms.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 2%
Germany 1 2%
Brazil 1 2%
Unknown 52 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 33%
Student > Ph. D. Student 10 18%
Other 6 11%
Student > Bachelor 5 9%
Student > Master 5 9%
Other 6 11%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 25%
Biochemistry, Genetics and Molecular Biology 10 18%
Pharmacology, Toxicology and Pharmaceutical Science 5 9%
Medicine and Dentistry 5 9%
Chemistry 4 7%
Other 11 20%
Unknown 6 11%