Abstract
Motivation: Gene prediction in metagenomic sequences remains a difficult problem. Current sequencing technologies do not achieve sufficient coverage to assemble the individual genomes in a typical sample; consequently, sequencing runs produce a large number of short sequences whose exact origin is unknown. Since these sequences are usually smaller than the average length of a gene, algorithms must make predictions based on very little data.Results: We present MetaProdigal, a metagenomic version of the gene prediction program Prodigal, that can identify genes in short, anonymous coding sequences with a high degree of accuracy. The novel value of the method consists of enhanced translation initiation site identification, ability to identify sequences that use alternate genetic codes and confidence values for each gene call. We compare the results of MetaProdigal with other methods and conclude with a discussion of future improvements.
| Original language | English |
|---|---|
| Article number | bts429 |
| Pages (from-to) | 2223-2230 |
| Number of pages | 8 |
| Journal | Bioinformatics |
| Volume | 28 |
| Issue number | 17 |
| DOIs | |
| State | Published - Sep 2012 |
Funding
Funding: Genomic Science Program, US Department of Energy, Office of Science, Biological and Environmental Research, a part of the Plant Microbial Interfaces Scientific Focus Area (http:// pmi.ornl.gov/), the BioEnergy Science Center, which is a US Department of Energy Bioenergy Research Center supported by the Office of Biological and Environmental Research in the DOE Office of Science and Oak Ridge National Laboratory is managed by UT Battelle, LLC, for the DOE (DE-AC05-00OR22725).
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