Scipediacontent at 14:22, 5 March 2021

2021-03-05T14:22:41Z

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2021-02-01T23:45:36Z

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Scipediacontent: Created page with "== Abstract == Background There has been an enormous expansion of use of chromatin immunoprecipitation followed by sequencing (ChIP-seq) technologies. Analysis of large-scale..."

2021-02-01T23:45:30Z

Created page with "== Abstract == Background There has been an enormous expansion of use of chromatin immunoprecipitation followed by sequencing (ChIP-seq) technologies. Analysis of large-scale..."

New page

== Abstract ==

Background There has been an enormous expansion of use of chromatin immunoprecipitation followed by sequencing (ChIP-seq) technologies. Analysis of large-scale ChIP-seq datasets involves a complex series of steps and production of several specialized graphical outputs. A number of systems have emphasized custom development of ChIP-seq pipelines. These systems are primarily based on custom programming of a single, complex pipeline or supply libraries of modules and do not produce the full range of outputs commonly produced for ChIP-seq datasets. It is desirable to have more comprehensive pipelines, in particular ones addressing common metadata tasks, such as pathway analysis, and pipelines producing standard complex graphical outputs. It is advantageous if these are highly modular systems, available as both turnkey pipelines and individual modules, that are easily comprehensible, modifiable and extensible to allow rapid alteration in response to new analysis developments in this growing area. Furthermore, it is advantageous if these pipelines allow data provenance tracking. Results We present a set of 20 ChIP-seq analysis software modules implemented in the Kepler workflow system; most (18/20) were also implemented as standalone, fully functional R scripts. The set consists of four full turnkey pipelines and 16 component modules. The turnkey pipelines in Kepler allow data provenance tracking. Implementation emphasized use of common R packages and widely-used external tools (e.g., MACS for peak finding), along with custom programming. This software presents comprehensive solutions and easily repurposed code blocks for ChIP-seq analysis and pipeline creation. Tasks include mapping raw reads, peakfinding via MACS, summary statistics, peak location statistics, summary plots centered on the transcription start site (TSS), gene ontology, pathway analysis, and de novo motif finding, among others. Conclusions These pipelines range from those performing a single task to those performing full analyses of ChIP-seq data. The pipelines are supplied as both Kepler workflows, which allow data provenance tracking, and, in the majority of cases, as standalone R scripts. These pipelines are designed for ease of modification and repurposing.

== Original document ==

The different versions of the original document can be found in:

* [http://dx.doi.org/10.1186/s12859-016-1125-3 http://dx.doi.org/10.1186/s12859-016-1125-3]

* [http://europepmc.org/articles/PMC4932705 http://europepmc.org/articles/PMC4932705]

* [https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-016-1125-3 https://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/s12859-016-1125-3] under the license cc-by

* [https://dx.doi.org/10.1186/s12859-016-1125-3 https://dx.doi.org/10.1186/s12859-016-1125-3]

* [http://link.springer.com/content/pdf/10.1186/s12859-016-1125-3 http://link.springer.com/content/pdf/10.1186/s12859-016-1125-3],
: [http://dx.doi.org/10.1186/s12859-016-1125-3 http://dx.doi.org/10.1186/s12859-016-1125-3]

* [https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1125-3 https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1125-3],
: [https://dblp.uni-trier.de/db/journals/bmcbi/bmcbi17.html#CormierKB16 https://dblp.uni-trier.de/db/journals/bmcbi/bmcbi17.html#CormierKB16],
: [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4932705 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4932705],
: [https://link.springer.com/article/10.1186/s12859-016-1125-3 https://link.springer.com/article/10.1186/s12859-016-1125-3],
: [https://core.ac.uk/display/81072822 https://core.ac.uk/display/81072822],
: [https://paperity.org/p/77386376/reusable-extensible-and-modifiable-r-scripts-and-kepler-workflows-for-comprehensive https://paperity.org/p/77386376/reusable-extensible-and-modifiable-r-scripts-and-kepler-workflows-for-comprehensive],
: [https://academic.microsoft.com/#/detail/2467978015 https://academic.microsoft.com/#/detail/2467978015]

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	: [https://paperity.org/p/77386376/reusable-extensible-and-modifiable-r-scripts-and-kepler-workflows-for-comprehensive https://paperity.org/p/77386376/reusable-extensible-and-modifiable-r-scripts-and-kepler-workflows-for-comprehensive],		: [https://paperity.org/p/77386376/reusable-extensible-and-modifiable-r-scripts-and-kepler-workflows-for-comprehensive https://paperity.org/p/77386376/reusable-extensible-and-modifiable-r-scripts-and-kepler-workflows-for-comprehensive],
	: [https://academic.microsoft.com/#/detail/2467978015 https://academic.microsoft.com/#/detail/2467978015]		: [https://academic.microsoft.com/#/detail/2467978015 https://academic.microsoft.com/#/detail/2467978015]
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← Older revision	Revision as of 23:45, 1 February 2021
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2016d - Revision history

Scipediacontent at 14:22, 5 March 2021

Scipediacontent: Scipediacontent moved page Draft Content 893456412 to 2016d

Scipediacontent: Created page with "== Abstract == Background There has been an enormous expansion of use of chromatin immunoprecipitation followed by sequencing (ChIP-seq) technologies. Analysis of large-scale..."