Gene and translation initiation site prediction in metagenomic sequences.
BACKGROUND
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.


BACKGROUND
The Prodigal software is freely available under the General Public License from http://code.google.com/p/prodigal/.
Computational Biology and Bioinformatics Group, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA. hyattpd@ornl.gov
Doug
D
Hyatt
Philip F
PF
LoCascio
Loren J
LJ
Hauser
Edward C
EC
Uberbacher
D000465:Algorithms; D001483:Base Sequence; D003198:Computer Simulation; D056186:Metagenomics / Q000379:methods*; D008957:Models, Genetic; D009174:Mycoplasma / Q000235:genetics; D016366:Open Reading Frames; D010442:Peptide Chain Initiation, Translational; D017422:Sequence Analysis, DNA / Q000379:methods; D012984:Software