TagCleaner: Identification and removal of tag sequences from genomic and metagenomic datasets View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2010-12

AUTHORS

Robert Schmieder, Yan Wei Lim, Forest Rohwer, Robert Edwards

ABSTRACT

BACKGROUND: Sequencing metagenomes that were pre-amplified with primer-based methods requires the removal of the additional tag sequences from the datasets. The sequenced reads can contain deletions or insertions due to sequencing limitations, and the primer sequence may contain ambiguous bases. Furthermore, the tag sequence may be unavailable or incorrectly reported. Because of the potential for downstream inaccuracies introduced by unwanted sequence contaminations, it is important to use reliable tools for pre-processing sequence data. RESULTS: TagCleaner is a web application developed to automatically identify and remove known or unknown tag sequences allowing insertions and deletions in the dataset. TagCleaner is designed to filter the trimmed reads for duplicates, short reads, and reads with high rates of ambiguous sequences. An additional screening for and splitting of fragment-to-fragment concatenations that gave rise to artificial concatenated sequences can increase the quality of the dataset. Users may modify the different filter parameters according to their own preferences. CONCLUSIONS: TagCleaner is a publicly available web application that is able to automatically detect and efficiently remove tag sequences from metagenomic datasets. It is easily configurable and provides a user-friendly interface. The interactive web interface facilitates export functionality for subsequent data processing, and is available at http://edwards.sdsu.edu/tagcleaner. More... »

PAGES

341

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/1471-2105-11-341

DOI

http://dx.doi.org/10.1186/1471-2105-11-341

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1004595205

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/20573248


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