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Method Article
Matthew Berriman
Berriman Lab Group, Sanger Institute
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Once a genome has been sequenced, a challenging task is to predict protein-coding genes in the genome assembly. If several genomes of related species have been sequenced, it is desirable that the pipeline is scalable to multiple species, and will give consistent results across species. Here we describe a consistent, scalable and automated computational pipeline, based on the MAKER software, for prediction of protein-coding genes in parasitic worm (nematode and platyhelminth) genome assemblies. This protocol can be used to generate a relatively accurate and complete gene set, for a broad range of nematode and platyhelminth species. Furthermore, it does not require RNAseq data and does not require training using a curated set of genes of known structure.
Keywords
MAKER, Augustus, GeneMark, SNAP, RATT, genBlastG, gene-finding, annotation, gene prediction, gene models, gene set, parasites, genomes, assemblies, parasitic worms, helminths, nematodes, flatworms, platyhelminths, Nematoda, Platyhelminthes
Figure 1
The authors declare no competing financial interests.
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Method Article
Matthew Berriman
Berriman Lab Group, Sanger Institute
Corresponding Author
Version History
CURRENT STATUS: Posted
Version 1
Posted 14 May, 2018
No community comments so far
Metrics
Comments: 0
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Once a genome has been sequenced, a challenging task is to predict protein-coding genes in the genome assembly. If several genomes of related species have been sequenced, it is desirable that the pipeline is scalable to multiple species, and will give consistent results across species. Here we describe a consistent, scalable and automated computational pipeline, based on the MAKER software, for prediction of protein-coding genes in parasitic worm (nematode and platyhelminth) genome assemblies. This protocol can be used to generate a relatively accurate and complete gene set, for a broad range of nematode and platyhelminth species. Furthermore, it does not require RNAseq data and does not require training using a curated set of genes of known structure.
Figure 1
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