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Robust principal component analysis for accurate outlier sample detection in RNA-Seq data.

Xiaoying ChenBo ZhangTing WangAzad BonniGuoyan Zhao
Published in: BMC bioinformatics (2020)
rPCA implemented in the PcaGrid function is an accurate and objective method to detect outlier samples. It is well suited for high-dimensional data with small sample sizes like RNA-seq data. Outlier removal can significantly improve the performance of differential gene detection and downstream functional analysis.
Keyphrases
  • rna seq
  • single cell
  • electronic health record
  • big data
  • high resolution
  • loop mediated isothermal amplification
  • data analysis
  • genome wide
  • machine learning
  • transcription factor
  • sensitive detection