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      SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read

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          Abstract

          Background

          High-throughput automated sequencing has enabled an exponential growth rate of sequencing data. This requires increasing sequence quality and reliability in order to avoid database contamination with artefactual sequences. The arrival of pyrosequencing enhances this problem and necessitates customisable pre-processing algorithms.

          Results

          SeqTrim has been implemented both as a Web and as a standalone command line application. Already-published and newly-designed algorithms have been included to identify sequence inserts, to remove low quality, vector, adaptor, low complexity and contaminant sequences, and to detect chimeric reads. The availability of several input and output formats allows its inclusion in sequence processing workflows. Due to its specific algorithms, SeqTrim outperforms other pre-processors implemented as Web services or standalone applications. It performs equally well with sequences from EST libraries, SSH libraries, genomic DNA libraries and pyrosequencing reads and does not lead to over-trimming.

          Conclusions

          SeqTrim is an efficient pipeline designed for pre-processing of any type of sequence read, including next-generation sequencing. It is easily configurable and provides a friendly interface that allows users to know what happened with sequences at every pre-processing stage, and to verify pre-processing of an individual sequence if desired. The recommended pipeline reveals more information about each sequence than previously described pre-processors and can discard more sequencing or experimental artefacts.

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          Most cited references16

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          Repbase update: a database and an electronic journal of repetitive elements.

          J Jurka (2000)
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            DNA sequence quality trimming and vector removal.

            Most sequence comparison methods assume that the data being compared are trustworthy, but this is not the case with raw DNA sequences obtained from automatic sequencing machines. Nevertheless, sequence comparisons need to be done on them in order to remove vector splice sites and contaminants. This step is necessary before other genomic data processing stages can be carried out, such as fragment assembly or EST clustering. A specialized tool is therefore needed to solve this apparent dilemma. We have designed and implemented a program that specifically addresses the problem. This program, called LUCY, has been in use since 1998 at The Institute for Genomic Research (TIGR). During this period, many rounds of experience-driven modifications were made to LUCY to improve its accuracy and its ability to deal with extremely difficult input cases. We believe we have finally obtained a useful program which strikes a delicate balance among the many issues involved in the raw sequence cleaning problem, and we wish to share it with the research community. LUCY is available directly from TIGR (http://www.tigr.org/softlab). Academic users can download LUCY after accepting a free academic use license. Business users may need to pay a license fee to use LUCY for commercial purposes. Questions regarding the quality assessment module of LUCY should be directed to Michael Holmes (mholmes@tigr.org). Questions regarding other aspects of LUCY should be directed to Hui-Hsien Chou (hhchou@iastate.edu).
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              A new DNA sequence assembly program.

              We describe the Genome Assembly Program (GAP), a new program for DNA sequence assembly. The program is suitable for large and small projects, a variety of strategies and can handle data from a range of sequencing instruments. It retains the useful components of our previous work, but includes many novel ideas and methods. Many of these methods have been made possible by the program's completely new, and highly interactive, graphical user interface. The program provides many visual clues to the current state of a sequencing project and allows users to interact in intuitive and graphical ways with their data. The program has tools to display and manipulate the various types of data that help to solve and check difficult assemblies, particularly those in repetitive genomes. We have introduced the following new displays: the Contig Selector, the Contig Comparator, the Template Display, the Restriction Enzyme Map and the Stop Codon Map. We have also made it possible to have any number of Contig Editors and Contig Joining Editors running simultaneously even on the same contig. The program also includes a new 'Directed Assembly' algorithm and routines for automatically detecting unfinished segments of sequence, to which it suggests experimental solutions.
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                Author and article information

                Journal
                BMC Bioinformatics
                BMC Bioinformatics
                BioMed Central
                1471-2105
                2010
                20 January 2010
                : 11
                : 38
                Affiliations
                [1 ]Departamento de Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain
                [2 ]Plataforma Andaluza de Bioinformática, Universidad de Málaga, 29071 Málaga, Spain
                [3 ]Departamento de Biología Molecular y Bioquímica, Universidad de Málaga, 29071 Málaga, Spain
                [4 ]Departamento de Arquitectura de Computadores, Universidad de Málaga, Málaga, Spain
                Article
                1471-2105-11-38
                10.1186/1471-2105-11-38
                2832897
                20089148
                e75f99b0-ccca-4d76-8723-674ac381f5b5
                Copyright ©2010 Falgueras et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 4 June 2009
                : 20 January 2010
                Categories
                Software

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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