ArticleBMC bioinformatics2010
SeqTrim: a high-throughput pipeline for pre-processing any type of sequence read.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 92 papers.
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Who cites it
92 citing papers in PubMed.
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- Time Series Transcriptomic Analysis of Bronchoalveolar Lavage Cells from Piglets Infected with Virulent or Low-Virulent Porcine Reproductive and Respiratory Syndrome Virus 1.Journal of virology · 2022Article
- cDNA-detector: detection and removal of cDNA contamination in DNA sequencing libraries.BMC bioinformatics · 2021Article
- Detection of Persistent Viruses by High-Throughput Sequencing in Tomato and Pepper from Panama: Phylogenetic and Evolutionary Studies.Plants (Basel, Switzerland) · 2021Article
- Chemical interplay and complementary adaptative strategies toggle bacterial antagonism and co-existence.Cell reports · 2021Article
- Persistent Southern Tomato Virus (STV) Interacts with Cucumber Mosaic and/or Pepino Mosaic Virus in Mixed- Infections Modifying Plant Symptoms, Viral Titer and Small RNA Accumulation.Microorganisms · 2021Article
- A Large Tn7-like Transposon Confers Hyper-Resistance to Copper inApplied and environmental microbiology · 2021Article
- Read trimming has minimal effect on bacterial SNP-calling accuracy.Microbial genomics · 2020Article
- An improved de novo assembling and polishing of Solea senegalensis transcriptome shed light on retinoic acid signalling in larvae.Scientific reports · 2020Article
- Two Homologues of the Global Regulator Csr/Rsm Redundantly Control Phaseolotoxin Biosynthesis and Virulence in the Plant PathogenMicroorganisms · 2020Article
- Molecular study of drought response in the Mediterranean coniferEcology and evolution · 2020Article
32 more citing papers are in PubMed but not listed here.
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6 authors.
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Abstract
backgroundHigh-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.
resultsSeqTrim 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.
conclusionsSeqTrim 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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