Pairagon+N-SCAN_EST: a model-based gene annotation pipeline View Full Text


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Article Info

DATE

2006-08-07

AUTHORS

Manimozhiyan Arumugam, Chaochun Wei, Randall H Brown, Michael R Brent

ABSTRACT

BackgroundThis paper describes Pairagon+N-SCAN_EST, a gene annotation pipeline that uses only native alignments. For each expressed sequence it chooses the best genomic alignment. Systems like ENSEMBL and ExoGean rely on trans alignments, in which expressed sequences are aligned to the genomic loci of putative homologs. Trans alignments contain a high proportion of mismatches, gaps, and/or apparently unspliceable introns, compared to alignments of cDNA sequences to their native loci. The Pairagon+N-SCAN_EST pipeline's first stage is Pairagon, a cDNA-to-genome alignment program based on a PairHMM probability model. This model relies on prior knowledge, such as the fact that introns must begin with GT, GC, or AT and end with AG or AC. It produces very precise alignments of high quality cDNA sequences. In the genomic regions between Pairagon's cDNA alignments, the pipeline combines EST alignments with de novo gene prediction by using N-SCAN_EST. N-SCAN_EST is based on a generalized HMM probability model augmented with a phylogenetic conservation model and EST alignments. It can predict complete transcripts by extending or merging EST alignments, but it can also predict genes in regions without EST alignments. Because they are based on probability models, both Pairagon and N-SCAN_EST can be trained automatically for new genomes and data sets.ResultsOn the ENCODE regions of the human genome, Pairagon+N-SCAN_EST was as accurate as any other system tested in the EGASP assessment, including ENSEMBL and ExoGean.ConclusionWith sufficient mRNA/EST evidence, genome annotation without trans alignments can compete successfully with systems like ENSEMBL and ExoGean, which use trans alignments. More... »

PAGES

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References to SciGraph publications

  • 2006-08-07. EGASP: the human ENCODE Genome Annotation Assessment Project in GENOME BIOLOGY
  • 2005. Using Multiple Alignments to Improve Gene Prediction in RESEARCH IN COMPUTATIONAL MOLECULAR BIOLOGY
  • 2003-10-17. Eval: A software package for analysis of genome annotations in BMC BIOINFORMATICS
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/gb-2006-7-s1-s5

    DOI

    http://dx.doi.org/10.1186/gb-2006-7-s1-s5

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1010895606

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/16925839


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