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Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data.

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).

SUBMITTER: Chen A

PROVIDER: S-EPMC9476399 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature

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Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data.

Chen Athena A Kammers Kai K Larman H Benjamin HB Scharpf Robert B RB Ruczinski Ingo I

BMC genomics 20220915 1

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-S ...[more]

PMID: 36109689

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Project description:This SuperSeries is composed of the SubSeries listed below.

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