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
    A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling
    • 157
    • PDF
    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
    RNA-Seq vs Dual- and Single-Channel Microarray Data: Sensitivity Analysis for Differential Expression and Clustering
    • 80
    • PDF
    Estimating accuracy of RNA-Seq and microarrays with proteomics
    • 303
    • PDF
    A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae
    • 298
    • PDF
    Measuring differential gene expression by short read sequencing: quantitative comparison to 2-channel gene expression microarrays
    • 179
    RNA‐Seq: A Method for Comprehensive Transcriptome Analysis
    • 267
    • PDF
    GC-Content Normalization for RNA-Seq Data
    • 485
    • PDF
    Mapping and quantifying mammalian transcriptomes by RNA-Seq
    • 10,587
    • PDF