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ADTGP: correcting single-cell antibody sequencing data using Gaussian process regression.

Alex C H Liu1,2, Steven M Chan1,2

  • 1Princess Margaret Cancer Centre, Toronto, Ontario, M5G 1L7, Canada.

Bioinformatics (Oxford, England)
|November 6, 2024
PubMed
Summary
This summary is machine-generated.

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We developed ADTGP, an R package for single-cell protein sequencing data analysis. It corrects technical noise using Gaussian process regression, enhancing data interpretability for researchers.

Area of Science:

  • Computational Biology
  • Bioinformatics
  • Single-cell Analysis

Background:

  • Single-cell protein sequencing generates complex data with technical noise.
  • Interpreting protein expression requires accurate noise correction.

Purpose of the Study:

  • Introduce ADTGP, an R package for correcting droplet-specific technical noise in single-cell protein sequencing data.
  • Enhance the interpretability of single-cell protein data.

Main Methods:

  • Utilizes Gaussian process regression to model and correct technical noise.
  • Models protein expression distribution conditioned on isotype control counts.
  • Requires raw protein counts, isotype control counts, and a design matrix.

Main Results:

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  • ADTGP effectively corrects droplet-specific technical noise.
  • Improved data interpretability is achieved through noise correction.
  • The package provides a robust method for analyzing single-cell protein data.

Conclusions:

  • ADTGP is a valuable R package for single-cell protein sequencing data analysis.
  • It offers a statistically sound approach to noise correction.
  • The package is accessible and user-friendly for researchers.