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).
Original language | English (US) |
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Article number | 654 |
Journal | BMC genomics |
Volume | 23 |
Issue number | 1 |
DOIs | |
State | Published - Dec 2022 |
Keywords
- Antobodies
- Bayesian Model
- Peptides
- Phage ImmunoPrecipitation Sequencing
- Reactivity
ASJC Scopus subject areas
- Genetics
- Biotechnology