Article

 

Assessing De Novo transcriptome assembly metrics for consistency and utility Public Deposited

Contenu téléchargeable

Télécharger le fichier PDF
https://ir.library.oregonstate.edu/concern/articles/5x21tm30z

This is the publisher’s final pdf. The published article is copyrighted by BioMed Central Ltd. and can be found at:  http://www.biomedcentral.com/.

Header

Attribute Name LabelAttribute Values Label
Creator
Abstract
  • Background: Transcriptome sequencing and assembly represent a great resource for the study of non-model species, and many metrics have been used to evaluate and compare these assemblies. Unfortunately, it is still unclear which of these metrics accurately reflect assembly quality. Results: We simulated sequencing transcripts of Drosophila melanogaster. By assembling these simulated reads using both a perfect and a modern transcriptome assembler while varying read length and sequencing depth, we evaluated quality metrics to determine whether they 1) revealed perfect assemblies to be of higher quality, and 2) revealed perfect assemblies to be more complete as data quantity increased. Several commonly used metrics were not consistent with these expectations, including average contig coverage and length, though they became consistent when singletons were included in the analysis. We found several annotation-based metrics to be consistent and informative, including contig reciprocal best hit count and contig unique annotation count. Finally, we evaluated a number of novel metrics such as reverse annotation count, contig collapse factor, and the ortholog hit ratio, discovering that each assess assembly quality in unique ways. Conclusions: Although much attention has been given to transcriptome assembly, little research has focused on determining how best to evaluate assemblies, particularly in light of the variety of options available for read length and sequencing depth. Our results provide an important review of these metrics and give researchers tools to produce the highest quality transcriptome assemblies.
License Label
Resource Type
Doi
Date available
Date issued
Bibliographic Citation
  • O'Neil, S. T., & Emrich, S. J. (2013). Assessing de novo transcriptome assembly metrics for consistency and utility. BMC Genomics, 14(1), 465-465. doi:10.1186/1471-2164-14-465
Has Journal
Has Volume
  • 14
Has Number
  • 1
Other Affiliation
Mot-clé
Déclaration de droits
Funding Statement
  • This work was supported in part by a fellowship to STO as part of theUniversity of Notre Dame’s strategic research investment in global health.
Publisher
Peerreviewed
Language
Replaces
Additional Information
  • description.provenance : Approved for entry into archive by Deborah Campbell(deborah.campbell@oregonstate.edu) on 2013-09-05T21:50:10Z (GMT) No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) OneilShawnTAssessingDeNovoTranscriptome.pdf: 3704774 bytes, checksum: 9f367bef7d8d813a552cc3bffc9f6005 (MD5)
  • description.provenance : Submitted by Deborah Campbell (deborah.campbell@oregonstate.edu) on 2013-09-05T21:48:34Z No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) OneilShawnTAssessingDeNovoTranscriptome.pdf: 3704774 bytes, checksum: 9f367bef7d8d813a552cc3bffc9f6005 (MD5)
  • description.provenance : Made available in DSpace on 2013-09-05T21:50:10Z (GMT). No. of bitstreams: 2 license_rdf: 1370 bytes, checksum: cd1af5ab51bcc7a5280cf305303530e9 (MD5) OneilShawnTAssessingDeNovoTranscriptome.pdf: 3704774 bytes, checksum: 9f367bef7d8d813a552cc3bffc9f6005 (MD5) Previous issue date: 2013-07-09

Des relations

Relationships Parent Rows Label

Rows Empty Text

Dans Collection:

Articles