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Reconstruction Set Test (RESET): A computationally efficient method for single sample gene set testing based on randomized reduced rank reconstruction error.

Hildreth Robert Frost
Published in: PLoS computational biology (2024)
We have developed a new, and analytically novel, single sample gene set testing method called Reconstruction Set Test (RESET). RESET quantifies gene set importance based on the ability of set genes to reconstruct values for all measured genes. RESET is realized using a computationally efficient randomized reduced rank reconstruction algorithm (available via the RESET R package on CRAN) that can effectively detect patterns of differential abundance and differential correlation for self-contained and competitive scenarios. As demonstrated using real and simulated scRNA-seq data, RESET provides superior performance at a lower computational cost relative to other single sample approaches.
Keyphrases
  • genome wide
  • genome wide identification
  • double blind
  • open label
  • genome wide analysis
  • phase iii
  • placebo controlled
  • machine learning
  • randomized controlled trial
  • transcription factor
  • clinical trial
  • climate change