author_facet Lienhard, Matthias
Grimm, Christina
Morkel, Markus
Herwig, Ralf
Chavez, Lukas
Lienhard, Matthias
Grimm, Christina
Morkel, Markus
Herwig, Ralf
Chavez, Lukas
author Lienhard, Matthias
Grimm, Christina
Morkel, Markus
Herwig, Ralf
Chavez, Lukas
spellingShingle Lienhard, Matthias
Grimm, Christina
Morkel, Markus
Herwig, Ralf
Chavez, Lukas
Bioinformatics
MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
Computational Mathematics
Computational Theory and Mathematics
Computer Science Applications
Molecular Biology
Biochemistry
Statistics and Probability
author_sort lienhard, matthias
spelling Lienhard, Matthias Grimm, Christina Morkel, Markus Herwig, Ralf Chavez, Lukas 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btt650 <jats:title>Abstract</jats:title> <jats:p>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.</jats:p> <jats:p>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.</jats:p> <jats:p>Availability and implementation: The latest version of MEDIPS is available as version 1.12.0 and part of Bioconductor 2.13. The package comes with a manual containing detailed description of its functionality and is available at http://www.bioconductor.org.</jats:p> <jats:p>Contact: lienhard@molgen.mpg.de</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments Bioinformatics
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title MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_unstemmed MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_full MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_fullStr MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_full_unstemmed MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_short MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_sort medips: genome-wide differential coverage analysis of sequencing data derived from dna enrichment experiments
topic Computational Mathematics
Computational Theory and Mathematics
Computer Science Applications
Molecular Biology
Biochemistry
Statistics and Probability
url http://dx.doi.org/10.1093/bioinformatics/btt650
publishDate 2014
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description <jats:title>Abstract</jats:title> <jats:p>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.</jats:p> <jats:p>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.</jats:p> <jats:p>Availability and implementation: The latest version of MEDIPS is available as version 1.12.0 and part of Bioconductor 2.13. The package comes with a manual containing detailed description of its functionality and is available at http://www.bioconductor.org.</jats:p> <jats:p>Contact:  lienhard@molgen.mpg.de</jats:p> <jats:p>Supplementary information:  Supplementary data are available at Bioinformatics online.</jats:p>
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author Lienhard, Matthias, Grimm, Christina, Morkel, Markus, Herwig, Ralf, Chavez, Lukas
author_facet Lienhard, Matthias, Grimm, Christina, Morkel, Markus, Herwig, Ralf, Chavez, Lukas, Lienhard, Matthias, Grimm, Christina, Morkel, Markus, Herwig, Ralf, Chavez, Lukas
author_sort lienhard, matthias
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description <jats:title>Abstract</jats:title> <jats:p>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.</jats:p> <jats:p>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.</jats:p> <jats:p>Availability and implementation: The latest version of MEDIPS is available as version 1.12.0 and part of Bioconductor 2.13. The package comes with a manual containing detailed description of its functionality and is available at http://www.bioconductor.org.</jats:p> <jats:p>Contact:  lienhard@molgen.mpg.de</jats:p> <jats:p>Supplementary information:  Supplementary data are available at Bioinformatics online.</jats:p>
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spelling Lienhard, Matthias Grimm, Christina Morkel, Markus Herwig, Ralf Chavez, Lukas 1367-4811 1367-4803 Oxford University Press (OUP) Computational Mathematics Computational Theory and Mathematics Computer Science Applications Molecular Biology Biochemistry Statistics and Probability http://dx.doi.org/10.1093/bioinformatics/btt650 <jats:title>Abstract</jats:title> <jats:p>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.</jats:p> <jats:p>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.</jats:p> <jats:p>Availability and implementation: The latest version of MEDIPS is available as version 1.12.0 and part of Bioconductor 2.13. The package comes with a manual containing detailed description of its functionality and is available at http://www.bioconductor.org.</jats:p> <jats:p>Contact: lienhard@molgen.mpg.de</jats:p> <jats:p>Supplementary information: Supplementary data are available at Bioinformatics online.</jats:p> MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments Bioinformatics
spellingShingle Lienhard, Matthias, Grimm, Christina, Morkel, Markus, Herwig, Ralf, Chavez, Lukas, Bioinformatics, MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments, Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability
title MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_full MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_fullStr MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_full_unstemmed MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_short MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
title_sort medips: genome-wide differential coverage analysis of sequencing data derived from dna enrichment experiments
title_unstemmed MEDIPS: genome-wide differential coverage analysis of sequencing data derived from DNA enrichment experiments
topic Computational Mathematics, Computational Theory and Mathematics, Computer Science Applications, Molecular Biology, Biochemistry, Statistics and Probability
url http://dx.doi.org/10.1093/bioinformatics/btt650