Evidence map›Paper›PMID 24308000›Full record

ArticleBioMed research international2013

ASPic-GeneID: a lightweight pipeline for gene prediction and alternative isoforms detection.

Tyler Alioto, Ernesto Picardi, Roderic Guigó, Graziano Pesole

Abstract read
In one paragraph

Article in BioMed research international, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

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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.

Tyler AliotoCentre Nacional d'Anàlisi Genòmica (CNAG), Parc Científic de Barcelona, 08028 Barcelona, Spain.
Ernesto Picardi
Roderic Guigó
Graziano Pesole

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

New genomes are being sequenced at an increasingly rapid rate, far outpacing the rate at which manual gene annotation can be performed. Automated genome annotation is thus necessitated by this growth in genome projects; however, full-fledged annotation systems are usually home-grown and customized to a particular genome. There is thus a renewed need for accurate ab initio gene prediction methods. However, it is apparent that fully ab initio methods fall short of the required level of sensitivity and specificity for a quality annotation. Evidence in the form of expressed sequences gives the single biggest improvement in accuracy when used to inform gene predictions. Here, we present a lightweight pipeline for first-pass gene prediction on newly sequenced genomes. The two main components are ASPic, a program that derives highly accurate, albeit not necessarily complete, EST-based transcript annotations from EST alignments, and GeneID, a standard gene prediction program, which we have modified to take as evidence intron annotations. The introns output by ASPic CDS predictions is given to GeneID to constrain the exon-chaining process and produce predictions consistent with the underlying EST alignments. The pipeline was successfully tested on the entire C. elegans genome and the 44 ENCODE human pilot regions.

Indexed as

Molecular Sequence AnnotationSoftwareAlgorithmsAnimalsChromosome MappingComputational BiologyExonsExpressed Sequence TagsGenomeHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNA

Identifiers

PMID24308000
PMCPMC3838850

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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.