Pandey, Ram Vinay; Nolte, Viola; Boenigk, Jens; Schlotterer, Christian:
CANGS DB: a stand-alone web-based database tool for processing, managing and analyzing 454 data in biodiversity studies.
2011
In: BMC research notes, Band 4 (2011), S. 227
Artikel/Aufsatz in Zeitschrift / Fach: Biologie
Fakultät für Biologie » Allgemeine Botanik
Titel:
CANGS DB: a stand-alone web-based database tool for processing, managing and analyzing 454 data in biodiversity studies.
Autor(in):
Pandey, Ram Vinay; Nolte, Viola; Boenigk, Jens im Online-Personal- und -Vorlesungsverzeichnis LSF anzeigen; Schlotterer, Christian
Erscheinungsjahr
2011
Erschienen in:
BMC research notes, Band 4 (2011), S. 227
ISSN
DOI

Abstract:

BACKGROUND: Next generation sequencing (NGS) is widely used in metagenomic and transcriptomic analyses in biodiversity. The ease of data generation provided by NGS platforms has allowed researchers to perform these analyses on their particular study systems. In particular the 454 platform has become the preferred choice for PCR amplicon based biodiversity surveys because it generates the longest sequence reads. Nevertheless, the handling and organization of massive amounts of sequencing data poses a major problem for the research community, particularly when multiple researchers are involved in data acquisition and analysis. An integrated and user-friendly tool, which performs quality control, read trimming, PCR primer removal, and data organization is desperately needed, therefore, to make data interpretation fast and manageable. FINDINGS: We developed CANGS DB (Cleaning and Analyzing Next Generation Sequences DataBase) a flexible, stand alone and user-friendly integrated database tool. CANGS DB is specifically designed to organize and manage the massive amount of sequencing data arising from various NGS projects. CANGS DB also provides an intuitive user interface for sequence trimming and quality control, taxonomy analysis and rarefaction analysis. Our database tool can be easily adapted to handle multiple sequencing projects in parallel with different sample information, amplicon sizes, primer sequences, and quality thresholds, which makes this software especially useful for non-bioinformaticians. Furthermore, CANGS DB is especially suited for projects where multiple users need to access the data. CANGS DB is available at http://code.google.com/p/cangsdb/. CONCLUSION: CANGS DB provides a simple and user-friendly solution to process, store and analyze 454 sequencing data. Being a local database that is accessible through a user-friendly interface, CANGS DB provides the perfect tool for collaborative amplicon based biodiversity surveys without requiring prior bioinformatics skills.