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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
RNA-seq03:21

RNA-seq

RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
Before the discovery of RNA-seq, microarray-based methods and Sanger sequencing were used for transcriptome analysis. However, while microarray-based...

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DNA Microarrays: Sample Quality Control, Array Hybridization and Scanning
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Published on: March 15, 2011

Power of deep sequencing and agilent microarray for gene expression profiling study.

Lin Feng1, Hang Liu, Yu Liu

  • 1State Key Laboratory of Molecular Oncology, Cancer Institute Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100021, People's Republic of China. fenglin@cicams.ac.cn

Molecular Biotechnology
|May 1, 2010
PubMed
Summary

Digital Gene Expression (DGE) profiling and microarray analysis show high consistency, especially for abundant genes. While DGE offers an extendable dynamic range, microarrays remain practical for many researchers.

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Digital Gene Expression (DGE) tag profiling is a next-generation sequencing method for gene expression analysis.
  • Microarrays are a widely used platform for examining gene expression profiles.

Purpose of the Study:

  • To compare the data quality of microarray and DGE platforms.
  • To evaluate the performance of both technologies using an in vitro cell model.

Main Methods:

  • Gene expression profiling using both microarray and DGE platforms.
  • Analysis of detected genes, overlapping genes, and technical replicates.
  • Comparison of dynamic range and detection variance between platforms.

Main Results:

  • Microarray detected 17,362 genes; DGE detected 15,938 genes, with 13,221 overlapping.
  • Both platforms demonstrated high correlation (>0.99) and low variance (<9%) in technical replicates.
  • DGE has an extendable dynamic range, while microarray's is fixed; consistency was high for abundant genes.
  • Microarrays showed limitations in distinguishing expression variations for less abundant genes.

Conclusions:

  • Microarray and DGE technologies exhibit high consistency, particularly for abundant transcripts.
  • DGE offers advantages in dynamic range, but microarrays remain a stable and practical option for many biological research applications.
  • Microarrays may be gradually replaced by DGE or RNA-sequencing but retain utility for current research needs.