ArticleBMC genomics2008
Repeats and EST analysis for new organisms.
Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- MeShClust v3.0: high-quality clustering of DNA sequences using the mean shift algorithm and alignment-free identity scores.BMC genomics · 2022Article
- Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era.Plants (Basel, Switzerland) · 2020Review
- Identification of repetitive elements in the genome of Oreochromis niloticus: tilapia repeat masker.Marine biotechnology (New York, N.Y.) · 2010Article
- k-link EST clustering: evaluating error introduced by chimeric sequences under different degrees of linkage.Bioinformatics (Oxford, England) · 2009Article
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Authors and funding
2 authors.
Funding
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Abstract
backgroundRepeat masking is an important step in the EST analysis pipeline. For new species, genomic knowledge is scarce and good repeat libraries are typically unavailable. In these cases it is common practice to mask against known repeats from other species (i.e., model organisms). There are few studies that investigate the effectiveness of this approach, or attempt to evaluate the different methods for identifying and masking repeats.
resultsUsing zebrafish and medaka as example organisms, we show that accurate repeat masking is an important factor for obtaining a high quality clustering. Furthermore, we show that masking with standard repeat libraries based on curated genomic information from other species has little or no positive effect on the quality of the resulting EST clustering. Library based repeat masking which often constitutes a computational bottleneck in the EST analysis pipeline can therefore be reduced to species specific repeat libraries, or perhaps eliminated entirely. In contrast, substantially improved results can be achived by applying a repeat library derived from a partial reference clustering (e.g., from mapping sequences against a partially sequenced genome).
conclusionOf the methods explored, we find that the best EST clustering is achieved after masking with repeat libraries that are species specific. In the absence of such libraries, library-less masking gives results superior to the current practice of using cross-species, genome-based libraries.
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