Whole-exome sequencing & Disease-targeted sequencing are currently the major clinical applications of NGS, based on a timely and cost-effective consideration.
With the use of NGS technologies and the ongoing discovering of disease-associated genes, a series of gene panels were launched for
basic research and diagnostic tests, ranging from single gene to hundreds of genes.

Typically each disease-target test can identified tens to hundreds of variants. A standard analysis approach is to search online databases or
 to evaluate disease-causing potential of sequence alterations using existing tools to fully interpret the importance of each identified variant.
However, the fundamental inconsistencies inherited from diverse annotation sources, software packages and data formats have
complicated the subsequent analysis work, making data management, integration and comparison very difficult.

Vanno integrates information from a wide variety of biomedical databases, functional predictions from currently available evaluation
models and mutation landscapes from 18 TCGA cancer types.
A highly integrated framework that incorporates filtering, sorting, clustering and visual analytics
(e.g., Circos, Heatmap, Protein Domain, 3D structure ) modules is provided to facilitate simultaneous exploration of oncogenomics datasets at
different levels such as gene, variant, protein domain or 3D structure, which is crucial for the successful extraction of knowledge from
sequence alterations as well as translating biological insights into clinical applications.

Vanno now supports but not limit to 24 disease-targeted gene tests designed for two dominant NGS sequencers, Ion PGM and MiSeq,
providing a complete solution for targeted sequencing analysis. Vanno can process at least 100 samples at a time, and only takes few minutes
to complete a comparative analysis of 100 samples.

Vanno is freely available at http://cgts.cgu.edu.tw/vanno.


Reference If you use Vanno in your scientific research, please cite us:
Po-Jung Huang, Chi-Ching Lee, Bertrand Chin-Ming Tan, Yuan-Ming Yeh, Kuo-Yang Huang, Ruei-Chi Gan, Ting-Wen Chen, Cheng-Yang Lee, Sheng-Ting Yang, Chung-Shou Liao, Hsuan Liu* and Petrus Tang* Vanno: A Visualization-aided Variant Annotation Tool. Hum Mutat. 2014