Literature DB >> 21097156

Benchmarking of gene prediction programs for metagenomic data.

Non Yok1, Gail Rosen.   

Abstract

This manuscript presents the most rigorous benchmarking of gene annotation algorithms for metagenomic datasets to date. We compare three different programs: GeneMark, MetaGeneAnnotator (MGA) and Orphelia. The comparisons are based on their performances over simulated fragments from one hundred species of diverse lineages. We defined four different types of fragments; two types come from the inter- and intra-coding regions and the other types are from the gene edges. Hoff et al. used only 12 species in their comparison; therefore, their sample is too small to represent an environmental sample. Also, no predecessors has separately examined fragments that contain gene edges as opposed to intra-coding regions. General observations in our results are that performances of all these programs improve as we increase the length of the fragment. On the other hand, intra-coding fragments of our data show low annotation error in all of the programs if compared to the gene edge fragments. Overall, we found an upper-bound performance by combining all the methods.

Mesh:

Year:  2010        PMID: 21097156     DOI: 10.1109/IEMBS.2010.5627744

Source DB:  PubMed          Journal:  Annu Int Conf IEEE Eng Med Biol Soc        ISSN: 2375-7477


  4 in total

1.  Combining gene prediction methods to improve metagenomic gene annotation.

Authors:  Non G Yok; Gail L Rosen
Journal:  BMC Bioinformatics       Date:  2011-01-13       Impact factor: 3.169

Review 2.  Integrative workflows for metagenomic analysis.

Authors:  Efthymios Ladoukakis; Fragiskos N Kolisis; Aristotelis A Chatziioannou
Journal:  Front Cell Dev Biol       Date:  2014-11-19

3.  Reduce manual curation by combining gene predictions from multiple annotation engines, a case study of start codon prediction.

Authors:  Thomas H A Ederveen; Lex Overmars; Sacha A F T van Hijum
Journal:  PLoS One       Date:  2013-05-10       Impact factor: 3.240

4.  EBI Metagenomics in 2017: enriching the analysis of microbial communities, from sequence reads to assemblies.

Authors:  Alex L Mitchell; Maxim Scheremetjew; Hubert Denise; Simon Potter; Aleksandra Tarkowska; Matloob Qureshi; Gustavo A Salazar; Sebastien Pesseat; Miguel A Boland; Fiona M I Hunter; Petra Ten Hoopen; Blaise Alako; Clara Amid; Darren J Wilkinson; Thomas P Curtis; Guy Cochrane; Robert D Finn
Journal:  Nucleic Acids Res       Date:  2018-01-04       Impact factor: 16.971

  4 in total

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