| Title |
VDAP-GUI: a user-friendly pipeline for variant discovery and annotation of raw next-generation sequencing data
|
|---|---|
| Published in |
3 Biotech, February 2016
|
| DOI | 10.1007/s13205-016-0382-1 |
| Pubmed ID | |
| Authors |
Ramesh Menon, Namrata V. Patel, Amitbikram Mohapatra, Chaitanya G. Joshi |
| Abstract |
Even though next-generation sequencing (NGS) has become an invaluable tool in molecular biology, several laboratories with NGS facilities lack trained Bioinformaticians for data analysis. Here, focusing on the variant detection application of NGS analysis, we have developed a fully automated pipeline, namely Variant Discovery and Annotation Tool-Graphical User Interface (VDAP-GUI), which detects and annotates single nucleotide polymorphisms and insertions/deletions from raw sequence reads. VDAP-GUI consolidates several proven methods in each step such as quality control, trimming, mapping, variant detection and annotation. It supports multiple NGS platforms and has four methodological choices for variant detection. Further, it can re-analyze existing data with alternate thresholds and generates easily interpretable reports in html and tab-delimited formats. Using VDAP-GUI, we have analyzed a publically available human whole-exome sequence dataset. VDAP-GUI is developed using Perl/Tk programming, and is available for free download and use at http://sourceforge.net/projects/vdapgui/ . |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| China | 1 | 6% |
| Unknown | 17 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 4 | 22% |
| Student > Bachelor | 3 | 17% |
| Researcher | 3 | 17% |
| Student > Ph. D. Student | 2 | 11% |
| Professor | 1 | 6% |
| Other | 3 | 17% |
| Unknown | 2 | 11% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 5 | 28% |
| Computer Science | 4 | 22% |
| Social Sciences | 2 | 11% |
| Engineering | 2 | 11% |
| Unknown | 5 | 28% |
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 15 February 2017.
All research outputs
#15,361,255
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Outputs from 3 Biotech
#399
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Outputs of similar age
#238,108
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Outputs of similar age from 3 Biotech
#13
of 18 outputs
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