C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search

Background Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a c...

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Bibliographic Details
Published in:BMC bioinformatics Vol. 18; no. Suppl 10; pp. 392 - 24
Main Authors: Sowpati, Divya Tej, Srivastava, Surabhi, Dhawan, Jyotsna, Mishra, Rakesh K
Format: Journal Article
Language:English
Published: London BioMed Central 13.09.2017
BioMed Central Ltd
Springer Nature B.V
BMC
Subjects:
Algorithms
Binding sites
Bioinformatics
Biomedical and Life Sciences
Cell cycle
Chromatin
Chromatin state
Computational Biology/Bioinformatics
Computer Appl. in Life Sciences
Computers
Data analysis
Data processing
Data transfer (computers)
Datasets
Embryonic Stem Cells - metabolism
Epigenetic inheritance
Epigenetic patterns
Epigenetics
Epigenomics
Gene expression
Genes
Genetic engineering
Genome browser
Genomes
Genomics
Graphical user interface
HeLa Cells
Humans
Identification and classification
Integrated software
Internet
JavaScript
K562 Cells
Life Sciences
Microarrays
Mobile applications
Pattern search
Promoter Regions, Genetic - genetics
Software
Stem cells
Transcription, Genetic
Trends
User interface
Visualization
Web app
Web Browser
Visualization
Genome browser
RNA-seq
JavaScript
Epigenetic patterns
ChIP-seq
Web app
Chromatin state
ISSN:1471-2105, 1471-2105
Online Access:Get full text
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Summary:Background Comparative epigenomic analysis across multiple genes presents a bottleneck for bench biologists working with NGS data. Despite the development of standardized peak analysis algorithms, the identification of novel epigenetic patterns and their visualization across gene subsets remains a challenge. Results We developed a fast and interactive web app, C-State (Chromatin-State), to query and plot chromatin landscapes across multiple loci and cell types. C-State has an interactive, JavaScript-based graphical user interface and runs locally in modern web browsers that are pre-installed on all computers, thus eliminating the need for cumbersome data transfer, pre-processing and prior programming knowledge. Conclusions C-State is unique in its ability to extract and analyze multi-gene epigenetic information. It allows for powerful GUI-based pattern searching and visualization. We include a case study to demonstrate its potential for identifying user-defined epigenetic trends in context of gene expression profiles.
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ISSN:1471-2105
1471-2105
DOI:10.1186/s12859-017-1786-6