Dataset Information

Data Analysis WorkbeNch (DAWN).

ABSTRACT: Synchrotron light source facilities worldwide generate terabytes of data in numerous incompatible data formats from a wide range of experiment types. The Data Analysis WorkbeNch (DAWN) was developed to address the challenge of providing a single visualization and analysis platform for data from any synchrotron experiment (including single-crystal and powder diffraction, tomography and spectroscopy), whilst also being sufficiently extensible for new specific use case analysis environments to be incorporated (e.g. ARPES, PEEM). In this work, the history and current state of DAWN are presented, with two case studies to demonstrate specific functionality. The first is an example of a data processing and reduction problem using the generic tools, whilst the second shows how these tools can be targeted to a specific scientific area.

SUBMITTER: Basham M

PROVIDER: S-EPMC4416692 | biostudies-literature | 2015 May

REPOSITORIES: biostudies-literature

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Publications

Data Analysis WorkbeNch (DAWN).

Basham Mark M Filik Jacob J Wharmby Michael T MT Chang Peter C Y PC El Kassaby Baha B Gerring Matthew M Aishima Jun J Levik Karl K Pulford Bill C A BC Sikharulidze Irakli I Sneddon Duncan D Webber Matthew M Dhesi Sarnjeet S SS Maccherozzi Francesco F Svensson Olof O Brockhauser Sandor S Náray Gabor G Ashton Alun W AW

Journal of synchrotron radiation 20150402 3

Synchrotron light source facilities worldwide generate terabytes of data in numerous incompatible data formats from a wide range of experiment types. The Data Analysis WorkbeNch (DAWN) was developed to address the challenge of providing a single visualization and analysis platform for data from any synchrotron experiment (including single-crystal and powder diffraction, tomography and spectroscopy), whilst also being sufficiently extensible for new specific use case analysis environments to be i ...[more]

PMID: 25931106

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Project description:BackgroundTraditional methods for computational motif discovery often suffer from poor performance. In particular, methods that search for sequence matches to known binding motifs tend to predict many non-functional binding sites because they fail to take into consideration the biological state of the cell. In recent years, genome-wide studies have generated a lot of data that has the potential to improve our ability to identify functional motifs and binding sites, such as information about chromatin accessibility and epigenetic states in different cell types. However, it is not always trivial to make use of this data in combination with existing motif discovery tools, especially for researchers who are not skilled in bioinformatics programming.ResultsHere we present MotifLab, a general workbench for analysing regulatory sequence regions and discovering transcription factor binding sites and cis-regulatory modules. MotifLab supports comprehensive motif discovery and analysis by allowing users to integrate several popular motif discovery tools as well as different kinds of additional information, including phylogenetic conservation, epigenetic marks, DNase hypersensitive sites, ChIP-Seq data, positional binding preferences of transcription factors, transcription factor interactions and gene expression. MotifLab offers several data-processing operations that can be used to create, manipulate and analyse data objects, and complete analysis workflows can be constructed and automatically executed within MotifLab, including graphical presentation of the results.ConclusionsWe have developed MotifLab as a flexible workbench for motif analysis in a genomic context. The flexibility and effectiveness of this workbench has been demonstrated on selected test cases, in particular two previously published benchmark data sets for single motifs and modules, and a realistic example of genes responding to treatment with forskolin. MotifLab is freely available at http://www.motiflab.org.

Dataset Information

Data Analysis WorkbeNch (DAWN).

Publications

Data Analysis WorkbeNch (DAWN).

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