ArticleBioinformatics (Oxford, England)2009
Pairagon: a highly accurate, HMM-based cDNA-to-genome aligner.
Article in Bioinformatics (Oxford, England), 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 7 citations in OpenAlex.
- Coding exon-structure aware realigner (CESAR) utilizes genome alignments for accurate comparative gene annotation.Nucleic acids research · 2016Article
- ASPic-GeneID: a lightweight pipeline for gene prediction and alternative isoforms detection.BioMed research international · 2013Article
- Benchmarking spliced alignment programs including Spaln2, an extended version of Spaln that incorporates additional species-specific features.Nucleic acids research · 2012Article
- Comparative analysis of information contents relevant to recognition of introns in many species.BMC genomics · 2011Article
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4 authors at 1 institution in 1 country.
Funding
Abstract
motivationThe most accurate way to determine the intron-exon structures in a genome is to align spliced cDNA sequences to the genome. Thus, cDNA-to-genome alignment programs are a key component of most annotation pipelines. The scoring system used to choose the best alignment is a primary determinant of alignment accuracy, while heuristics that prevent consideration of certain alignments are a primary determinant of runtime and memory usage. Both accuracy and speed are important considerations in choosing an alignment algorithm, but scoring systems have received much less attention than heuristics.
resultsWe present Pairagon, a pair hidden Markov model based cDNA-to-genome alignment program, as the most accurate aligner for sequences with high- and low-identity levels. We conducted a series of experiments testing alignment accuracy with varying sequence identity. We first created 'perfect' simulated cDNA sequences by splicing the sequences of exons in the reference genome sequences of fly and human. The complete reference genome sequences were then mutated to various degrees using a realistic mutation simulator and the perfect cDNAs were aligned to them using Pairagon and 12 other aligners. To validate these results with natural sequences, we performed cross-species alignment using orthologous transcripts from human, mouse and rat. We found that aligner accuracy is heavily dependent on sequence identity. For sequences with 100% identity, Pairagon achieved accuracy levels of >99.6%, with one quarter of the errors of any other aligner. Furthermore, for human/mouse alignments, which are only 85% identical, Pairagon achieved 87% accuracy, higher than any other aligner. AVAILABILITY: Pairagon source and executables are freely available at http://mblab.wustl.edu/software/pairagon/
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