| Title |
C-State: an interactive web app for simultaneous multi-gene visualization and comparative epigenetic pattern search
|
|---|---|
| Published in |
BMC Bioinformatics, September 2017
|
| DOI | 10.1186/s12859-017-1786-6 |
| Pubmed ID | |
| Authors |
Divya Tej Sowpati, Surabhi Srivastava, Jyotsna Dhawan, Rakesh K Mishra |
| Abstract |
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. 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. 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. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 50% |
| Scientists | 1 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 41 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 24% |
| Student > Ph. D. Student | 7 | 17% |
| Researcher | 6 | 15% |
| Student > Bachelor | 5 | 12% |
| Professor | 5 | 12% |
| Other | 5 | 12% |
| Unknown | 3 | 7% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 14 | 34% |
| Agricultural and Biological Sciences | 7 | 17% |
| Computer Science | 7 | 17% |
| Neuroscience | 2 | 5% |
| Medicine and Dentistry | 2 | 5% |
| Other | 4 | 10% |
| Unknown | 5 | 12% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 November 2017.
All research outputs
#18,571,001
of 23,001,641 outputs
Outputs from BMC Bioinformatics
#6,349
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Outputs of similar age
#242,649
of 316,290 outputs
Outputs of similar age from BMC Bioinformatics
#84
of 101 outputs
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