Evidence map›Paper›PMID 16925839›Full record

ArticleGenome biology2006

Pairagon+N-SCAN_EST: a model-based gene annotation pipeline.

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

Abstract readEvaluation Study
In one paragraph

Article in Genome biology, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Manimozhiyan ArumugamLaboratory for Computational Genomics and Department of Computer Science, Washington University, One Brookings Drive, St, Louis, MO 63130, USA.
Chaochun Wei
Randall H Brown
Michael R Brent

Funding

The Encyclopedia of Genes and Gene VariantsU01HG003150 · NHGRI · MUNICIPAL INSTITUTE OF MEDICAL RESEARCH · PI GUIGO, RODERIC · 2003 to 2006
$2.1M
Predicting Gene Structure: Vertebrate Genome ComparisonR01HG002278 · NHGRI · WASHINGTON UNIVERSITY · PI BRENT, MICHAEL R · 2002 to 2008
$1.9M
NCI NIH HHS N01 CO012400NCI NIH HHS N01-CO-12400NHGRI NIH HHS R01 HG002278NHGRI NIH HHS R01 HG02278NHGRI NIH HHS U01 HG003150
6 · The paper itself

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.

Indexed as

Expressed Sequence TagsSequence AlignmentSoftwareBase SequenceComputational BiologyDNA, ComplementaryGenesGenome, HumanGenomicsHumansModels, StatisticalOpen Reading FramesPhylogenyRNA, MessengerDNA, ComplementaryRNA, Messenger

Identifiers

PMID16925839
PMCPMC1810554

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.