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Bioinformatics Advance Access originally published online on January 17, 2008
Bioinformatics 2008 24(4):462-467; doi:10.1093/bioinformatics/btm632
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© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Figaro: a novel statistical method for vector sequence removal

James Robert White 1,2, Michael Roberts 1,3, James A. Yorke 1,2,3 and Mihai Pop 1,*

1Center for Bioinformatics and Computational Biology, University of Maryland – College Park, MD 20742, 2Applied Mathematics and Scientific Computation Program, University of Maryland – College Park, MD 20742 and 3Institute for Physical Sciences and Technology, University of Maryland – College Park, MD 20742, USA

*To whom correspondence should be addressed.


  Abstract

Motivation: Sequences produced by automated Sanger sequencing machines frequently contain fragments of the cloning vector on their ends. Software tools currently available for identifying and removing the vector sequence require knowledge of the vector sequence, specific splice sites and any adapter sequences used in the experiment—information often omitted from public databases. Furthermore, the clipping coordinates themselves are missing or incorrectly reported. As an example, within the ~1.24 billion shotgun sequences deposited in the NCBI Trace Archive, as many as ~735 million (~60%) lack vector clipping information. Correct clipping information is essential to scientists attempting to validate, improve and even finish the increasingly large number of genomes released at a ‘draft’ quality level.

Results: We present here Figaro, a novel software tool for identifying and removing the vector from raw sequence data without prior knowledge of the vector sequence. The vector sequence is automatically inferred by analyzing the frequency of occurrence of short oligo-nucleotides using Poisson statistics. We show that Figaro achieves 99.98% sensitivity when tested on ~1.5 million shotgun reads from Drosophila pseudoobscura. We further explore the impact of accurate vector trimming on the quality of whole-genome assemblies by re-assembling two bacterial genomes from shotgun sequences deposited in the Trace Archive. Designed as a module in large computational pipelines, Figaro is fast, lightweight and flexible.

Availability: Figaro is released under an open-source license through the AMOS package (http://amos.sourceforge.net/Figaro).

Contact: mpop{at}umiacs.umd.edu

Associate Editor: John Quackenbush

Received on September 26, 2007; revised on November 21, 2007; accepted on December 17, 2007

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