ArticleNucleic acids research2003
A novel algorithm for computational identification of contaminated EST libraries.
Article in Nucleic acids research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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36 citing papers in PubMed.
- Molecular diversity and evolutionary trends of cysteine-rich peptides from the venom glands of Chinese spider Heteropoda venatoria.Scientific reports · 2021Article
- A comprehensive survey of non-canonical splice sites in the human transcriptome.Nucleic acids research · 2014Article
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- Using chimaeric expression sequence tag as the reference to identify three-dimensional chromosome contacts.DNA research : an international journal for rapid publication of reports on genes and genomes · 2013Article
- Identification of novel splice variants and exons of human endothelial cell-specific chemotaxic regulator (ECSCR) by bioinformatics analysis.Computational biology and chemistry · 2012Article
- No evidence for lateral gene transfer between salmonids and schistosomes.Nature genetics · 2010Article
- A novel human heparanase splice variant, T5, endowed with protumorigenic characteristics.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2010Article
- Leveraging skewed transcript abundance by RNA-Seq to increase the genomic depth of the tree of life.Proceedings of the National Academy of Sciences of the United States of America · 2010Article
- Quantitative gene expression profiles in real time from expressed sequence tag databases.Gene expression · 2010Article
- k-link EST clustering: evaluating error introduced by chimeric sequences under different degrees of linkage.Bioinformatics (Oxford, England) · 2009Article
- Noisy splicing, more than expression regulation, explains why some exons are subject to nonsense-mediated mRNA decay.BMC biology · 2009Article
- No-match ORESTES explored as tumor markers.Nucleic acids research · 2009Article
- CleanEST: a database of cleansed EST libraries.Nucleic acids research · 2009Article
- Modeling transcriptome based on transcript-sampling data.PloS one · 2008Article
- Human glycolipid transfer protein (GLTP) genes: organization, transcriptional status and evolution.BMC genomics · 2008Article
- ConiferEST: an integrated bioinformatics system for data reprocessing and mining of conifer expressed sequence tags (ESTs).BMC genomics · 2007Article
- Simultaneous identification of long similar substrings in large sets of sequences.BMC bioinformatics · 2007Article
- Tentative mapping of transcription-induced interchromosomal interaction using chimeric EST and mRNA data.PloS one · 2007Article
- Characterization and predictive discovery of evolutionarily conserved mammalian alternative promoters.Genome research · 2007Article
- Under-representation of PolyA/PolyT tailed ESTs in human ESTdb: an obstacle to alternative polyadenylation inference.Bioinformation · 2006Article
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2 authors.
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Abstract
A key goal of the Human Genome Project was to understand the complete set of human proteins, the proteome. Since the genome sequence by itself is not sufficient for predicting new genes and alternative splicing events that lead to new proteins, expressed sequence tags (ESTs) are used as the primary tool for these purposes. The high prevalence of artifacts in dbEST, however, often leads to invalid predictions. Here we describe a novel method for recognizing genomic DNA contamination and other artifacts that cannot be identified using current EST cleaning techniques. Our method uses the alignment of the entire set of ESTs to the human genome to identify highly contaminated EST libraries. We discovered 53 highly contaminated libraries and a subset of 24 766 ESTs from these libraries that probably represent contamination with genomic DNA, pre-mRNA, and ESTs that span non-canonical introns. Although this is only a small fraction of the entire EST dataset, each contaminating sequence could create a spurious transcript prediction. Indeed, in the clustering and assembly tool that we used, these sequences would have caused incorrect inference of 9575 new splice variants and 6370 new genes. Conclusions based on EST analysis, including prediction of alternative splicing, should be re-evaluated in light of these results. Our method, along with the identified set of contaminated sequences, will be essential for applications that depend on large EST datasets.
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