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Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data.
Chen, Athena; Kammers, Kai; Larman, H Benjamin; Scharpf, Robert B; Ruczinski, Ingo.
Afiliação
  • Chen A; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  • Kammers K; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, USA.
  • Larman HB; Department of Pathology and the Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, USA.
  • Scharpf RB; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, USA.
  • Ruczinski I; Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. ingo@jhu.edu.
BMC Genomics ; 23(1): 654, 2022 Sep 15.
Article em En | MEDLINE | ID: mdl-36109689
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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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bacteriófagos Tipo de estudo: Prognostic_studies Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Bacteriófagos Tipo de estudo: Prognostic_studies Idioma: En Revista: BMC Genomics Assunto da revista: GENETICA Ano de publicação: 2022 Tipo de documento: Article País de afiliação: Estados Unidos