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Benchmarking differential expression analysis tools for RNA-Seq: normalization-based vs. log-ratio transformation-based methods.

Thomas P QuinnTamsyn M CrowleyMark F Richardson
Published in: BMC bioinformatics (2018)
Our results suggest that log-ratio transformation-based methods can work to measure differential expression from RNA-Seq data, provided that certain assumptions are met. Moreover, these methods have very high precision (i.e., few false positives) in simulations and perform well on real data too. With previously demonstrated applicability to 16S rRNA data, ALDEx2 can thus serve as a single tool for data from multiple sequencing modalities.
Keyphrases
  • rna seq
  • single cell
  • electronic health record
  • big data
  • machine learning
  • artificial intelligence
  • molecular dynamics
  • monte carlo