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 edgeR1 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).
Competing Interest Statement
H.B.L. is an inventor on a patent describing the VirScan technology (US patent no. 15/105,722). H.B.L. is a founder of Portal Bioscience, Alchemab and ImmuneID, and is an advisor to TScan Therapeutics. R.B.S. is a founder and consultant of Delfi Diagnostics, and owns Delfi Diagnostics stock subject to certain restrictions under university policy. Johns Hopkins University owns equity in Delfi Diagnostics.