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Related Concept Videos

RNA-seq03:21

RNA-seq

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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...
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DNA Microarrays02:34

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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...
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Rup (RNA-seq Usability Assessment Pipeline) - Quality Control for Bulk RNA-seq Experiments in Eukaryotes
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Correlation between RNA-Seq and microarrays results using TCGA data.

Li Chen1, Fenghao Sun2, Xiaodong Yang2

  • 1Department of Thoracic Surgery, Zhongshan Hospital, Fudan University, Shanghai, 20032, China; Department of Orthopedics, West China Hospital, Sichuan University, Chengdu, Sichuan, 610041, China.

Gene
|July 24, 2017
PubMed
Summary
This summary is machine-generated.

RNA sequencing (RNA-Seq) and microarrays show high reproducibility for transcriptome profiling. Most genes detected by both methods correlate well, indicating reliable results for most transcripts.

Keywords:
MicroarrayRNA-SeqTCGATranscript expression

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • RNA sequencing (RNA-Seq) and microarrays are key technologies for transcriptome profiling.
  • Both methods have distinct advantages and limitations.
  • Understanding their concordance is crucial for accurate gene expression analysis.

Purpose of the Study:

  • To assess the correlation and reproducibility between RNA-Seq and microarray data.
  • To compare transcript detection across different platforms using the same samples.
  • To evaluate the reliability of these technologies in gene expression studies.

Main Methods:

  • Utilized The Cancer Genome Atlas (TCGA) data for lung squamous cell carcinoma.
  • Analyzed RNA-Seq v2 and three distinct microarray platforms.
  • Applied Pearson correlation analysis to 11,120 genes across 111 samples.

Main Results:

  • A significant correlation was observed for 89.8% of genes between RNA-Seq and microarrays.
  • High correlation (R≥0.8) was found in 29.3% of genes across all comparisons.
  • Discrepancies were more pronounced for transcripts with extremely high or low expression levels.

Conclusions:

  • RNA-Seq and microarrays demonstrate high reproducibility for the majority of transcripts.
  • The findings support the reliability of both technologies for transcriptome profiling.
  • Careful consideration of expression levels is advised when comparing results across platforms.