Improved Annotation of Fungal Genomes with Kingdom-Specific HMM Library
Author Information
Author(s): Alam Intikhab, Hubbard Simon J, Oliver Stephen G, Rattray Magnus
Primary Institution: University of Manchester
Hypothesis
Are kingdom-specific HMMs more effective for annotating fungal genomes compared to general models?
Conclusion
Kingdom-specific models provide improved coverage for annotating fungal genomes, especially when used in combination with general models.
Supporting Evidence
- FPfam showed 64.29% coverage compared to 56.55% with Pfam for the original 30 genomes.
- Combining FPfam and Pfam improved coverage to 65.60%.
- FPfam detected 24,878 sequences missed by Pfam.
Takeaway
This study created a special library to help find more parts of fungal genes, showing that using specific tools can help scientists understand fungi better.
Methodology
The study constructed a fungal-specific HMM library using sequences from 30 genomes and evaluated its performance against five new genomes.
Limitations
Some sequences found by the general Pfam model may be missed by the specific FPfam model.
Digital Object Identifier (DOI)
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