Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells

@article{Zhao2014ComparisonOR,
  title={Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells},
  author={S. Zhao and W. Fung-Leung and A. Bittner and K. Ngo and X. Liu},
  journal={PLoS ONE},
  year={2014},
  volume={9}
}
  • S. Zhao, W. Fung-Leung, +2 authors X. Liu
  • Published 2014
  • Biology, Medicine
  • PLoS ONE
  • To demonstrate the benefits of RNA-Seq over microarray in transcriptome profiling, both RNA-Seq and microarray analyses were performed on RNA samples from a human T cell activation experiment. In contrast to other reports, our analyses focused on the difference, rather than similarity, between RNA-Seq and microarray technologies in transcriptome profiling. A comparison of data sets derived from RNA-Seq and Affymetrix platforms using the same set of samples showed a high correlation between gene… CONTINUE READING
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    References

    SHOWING 1-10 OF 45 REFERENCES
    RNA-seq: an assessment of technical reproducibility and comparison with gene expression arrays.
    • 2,585
    • PDF
    Bias detection and correction in RNA-Sequencing data
    • 142
    • PDF
    Estimating accuracy of RNA-Seq and microarrays with proteomics
    • 303
    • PDF
    RNA‐Seq: A Method for Comprehensive Transcriptome Analysis
    • 267
    • PDF
    GC-Content Normalization for RNA-Seq Data
    • 485
    • PDF