title: Benchmarking of gene prediction programs for metagenomic data.
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.
authors.affiliation: Drexel University, Electrical and Computer Engineering Department, 3141 Chestnut Street, PA 19104, USA. ng39@drexel.edu
authors.forename: Non
authors.initials: N
authors.lastname: Yok
authors.forename: Gail
authors.initials: G
authors.lastname: Rosen
mesh_terms: D000465:Algorithms; D019985:Benchmarking; D030541:Databases, Genetic; D056186:Metagenomics / Q000379:methods*; D058977:Molecular Sequence Annotation / Q000379:methods*; D012372:ROC Curve