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Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data
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 impo...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476399/ https://www.ncbi.nlm.nih.gov/pubmed/36109689 http://dx.doi.org/10.1186/s12864-022-08869-y |
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author | Chen, Athena Kammers, Kai Larman, H Benjamin Scharpf, Robert B. Ruczinski, Ingo |
author_facet | Chen, Athena Kammers, Kai Larman, H Benjamin Scharpf, Robert B. Ruczinski, Ingo |
author_sort | Chen, Athena |
collection | PubMed |
description | 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). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08869-y. |
format | Online Article Text |
id | pubmed-9476399 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-94763992022-09-15 Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data Chen, Athena Kammers, Kai Larman, H Benjamin Scharpf, Robert B. Ruczinski, Ingo BMC Genomics Research 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). SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-022-08869-y. BioMed Central 2022-09-15 /pmc/articles/PMC9476399/ /pubmed/36109689 http://dx.doi.org/10.1186/s12864-022-08869-y Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Chen, Athena Kammers, Kai Larman, H Benjamin Scharpf, Robert B. Ruczinski, Ingo Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data |
title | Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data |
title_full | Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data |
title_fullStr | Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data |
title_full_unstemmed | Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data |
title_short | Detecting antibody reactivities in Phage ImmunoPrecipitation Sequencing data |
title_sort | detecting antibody reactivities in phage immunoprecipitation sequencing data |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9476399/ https://www.ncbi.nlm.nih.gov/pubmed/36109689 http://dx.doi.org/10.1186/s12864-022-08869-y |
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