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  AutoRELACS: Automated Generation And Analysis of Ultra-parallel ChIP-seq

Arrigoni, L., Ferrari, F., Weller, J., Bella, C., Bönisch, U., & Manke, T. (2020). AutoRELACS: Automated Generation And Analysis of Ultra-parallel ChIP-seq. Scientific Reports, 10, 12400. doi:org/10.1101/2020.03.30.016287.

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Arrigoni, Laura1, Author
Ferrari, Fernando1, Author
Weller, J.1, Author
Bella, Chiara1, Author
Bönisch, Ulrike1, Author           
Manke, Thomas1, Author           
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1Max Planck Institute of Immunobiology and Epigenetics, Max Planck Society, ou_2243648              

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 Abstract: Chromatin immunoprecipitation followed by sequencing (ChIP-seq) is a method used to profile protein-DNA interactions genome-wide. RELACS (Restriction Enzyme-based Labeling of Chromatin in Situ) is a recently developed ChIP-seq protocol that deploys a chromatin barcoding strategy to enable standardized and high-throughput generation of ChIP-seq data. The manual implementation of RELACS is constrained by human processivity in both data generation and data analysis. To overcome these limitations, we have developed AutoRELACS, an automated implementation of the RELACS protocol using the liquid handler Biomek i7 workstation. We match the unprecedented processivity in data generation allowed by AutoRELACS with the automated computation pipelines offered by snakePipes. In doing so, we build a continuous workflow that streamlines epigenetic profiling, from sample collection to biological interpretation. Here, we show that AutoRELACS successfully automates chromatin barcode integration, and is able to generate high-quality ChIP-seq data comparable with the standards of the manual protocol, also for limited amounts of biological samples.

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Language(s): eng - English
 Dates: 2020-04-01
 Publication Status: Published online
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 Rev. Type: No review
 Identifiers: DOI: org/10.1101/2020.03.30.016287
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Title: Scientific Reports
  Abbreviation : Sci. Rep.
Source Genre: Journal
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Publ. Info: London, UK : Nature Publishing Group
Pages: - Volume / Issue: 10 Sequence Number: - Start / End Page: 12400 Identifier: ISSN: 2045-2322
CoNE: https://pure.mpg.de/cone/journals/resource/2045-2322