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Cytomulate: accurate and efficient simulation of CyTOF data.

Yuqiu YangKaiwen WangZeyu LuTao WangXinlei Wang
Published in: Genome biology (2023)
Recently, many analysis tools have been devised to offer insights into data generated via cytometry by time-of-flight (CyTOF). However, objective evaluations of these methods remain absent as most evaluations are conducted against real data where the ground truth is generally unknown. In this paper, we develop Cytomulate, a reproducible and accurate simulation algorithm of CyTOF data, which could serve as a foundation for future method development and evaluation. We demonstrate that Cytomulate can capture various characteristics of CyTOF data and is superior in learning overall data distributions than single-cell RNA-seq-oriented methods such as scDesign2, Splatter, and generative models like LAMBDA.
Keyphrases
  • single cell
  • rna seq
  • electronic health record
  • big data
  • machine learning
  • deep learning
  • high resolution
  • high throughput