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MEDIPS: genome wide differential coverage analysis of sequencing data derived from DNA enrichment experiments

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Lienhard,  Matthias
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Grimm,  Christina
In vitro Ligand Screening (Zoltán Konthur), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Morkel,  Markus
Dept. of Developmental Genetics (Head: Bernhard G. Herrmann), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Herwig,  Ralf
Bioinformatics (Ralf Herwig), Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Chavez,  Lukas
Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society;

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Citation

Lienhard, M., Grimm, C., Morkel, M., Herwig, R., & Chavez, L. (2014). MEDIPS: genome wide differential coverage analysis of sequencing data derived from DNA enrichment experiments. Bioinformatics, 30(2), 284-286. doi:10.1093/bioinformatics/btt650.


Cite as: https://hdl.handle.net/21.11116/0000-0001-01E5-B
Abstract
Motivation: DNA enrichment followed by sequencing is a versatile tool in molecular biology, with a wide variety of applications including genome-wide analysis of epigenetic marks and mechanisms. A common requirement of these diverse applications is a comparison of read coverage between experimental conditions. The amount of samples generated for such comparisons ranges from few replicates to hundreds of samples per condition for epigenome-wide association studies. Consequently, there is an urgent need for software that allows for fast and simple processing and comparison of sequencing data derived from enriched DNA. Results: Here, we present a major update of the R/Bioconductor package MEDIPS, which allows for an arbitrary number of replicates per group and integrates sophisticated statistical methods for the detection of differential coverage between experimental conditions. Our approach can be applied to a diversity of quantitative sequencing data. In addition, our update adds novel functionality to MEDIPS, including correlation analysis between samples, and takes advantage of Bioconductor’s annotation databases to facilitate annotation of specific genomic regions.