BMC Genomics (Sep 2022)

Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data

  • Athena Chen,
  • Kai Kammers,
  • H Benjamin Larman,
  • Robert B. Scharpf,
  • Ingo Ruczinski

DOI
https://doi.org/10.1186/s12864-022-08869-y
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 11

Abstract

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Abstract Phage ImmunoPrecipitation Sequencing (PhIP-Seq) is a recently developed technology to assess antibody reactivity, quantifying antibody binding towards hundreds of thousands of candidate epitopes. The output from PhIP-Seq experiments are read count matrices, similar to RNA-Seq data; however some important differences do exist. In this manuscript we investigated whether the publicly available method edgeR (Robinson et al., Bioinformatics 26(1):139–140, 2010) for normalization and analysis of RNA-Seq data is also suitable for PhIP-Seq data. We find that edgeR is remarkably effective, but improvements can be made and introduce a Bayesian framework specifically tailored for data from PhIP-Seq experiments (Bayesian Enrichment Estimation in R, BEER).

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