ArticleNucleic acids research1995
A frameshift error detection algorithm for DNA sequencing projects.
Article in Nucleic acids research, 1995. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 30 citations in OpenAlex.
- An approach for searching insertions in bacterial genes leading to the phase shift of triplet periodicity.Genomics, proteomics & bioinformatics · 2011Article
- Comparative proteogenomics: combining mass spectrometry and comparative genomics to analyze multiple genomes.Genome research · 2008Article
- Predicting genes expressed via -1 and +1 frameshifts.Nucleic acids research · 2004Article
- Use and misuse of correspondence analysis in codon usage studies.Nucleic acids research · 2002Article
- Current methods of gene prediction, their strengths and weaknesses.Nucleic acids research · 2002Review
- Detecting and analyzing DNA sequencing errors: toward a higher quality of the Bacillus subtilis genome sequence.Genome research · 1999Article
- PairWise and SearchWise: finding the optimal alignment in a simultaneous comparison of a protein profile against all DNA translation frames.Nucleic acids research · 1996Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
During the determination of DNA sequences, frameshift errors are not the most frequent but they are the most bothersome as they corrupt the amino acid sequence over several residues. Detection of such errors by sequence alignment is only possible when related sequences are found in the databases. To avoid this limitation, we have developed a new tool based on the distribution of non-overlapping 3-tuples or 6-tuples in the three frames of an ORF. The method relies upon the result of a correspondence analysis. It has been extensively tested on Bacillus subtilis and Saccharomyces cerevisiae sequences and has also been examined with human sequences. The results indicate that it can detect frameshift errors affecting as few as 20 bp with a low rate of false positives (no more than 1.0/1000 bp scanned). The proposed algorithm can be used to scan a large collection of data, but it is mainly intended for laboratory practice as a tool for checking the quality of the sequences produced during a sequencing project.
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