Parameters for accurate genome alignment.
BACKGROUND
Genome sequence alignments form the basis of much research. Genome alignment depends on various mundane but critical choices, such as how to mask repeats and which score parameters to use. Surprisingly, there has been no large-scale assessment of these choices using real genomic data. Moreover, rigorous procedures to control the rate of spurious alignment have not been employed.


RESULTS
We have assessed 495 combinations of score parameters for alignment of animal, plant, and fungal genomes. As our gold-standard of accuracy, we used genome alignments implied by multiple alignments of proteins and of structural RNAs. We found the HOXD scoring schemes underlying alignments in the UCSC genome database to be far from optimal, and suggest better parameters. Higher values of the X-drop parameter are not always better. E-values accurately indicate the rate of spurious alignment, but only if tandem repeats are masked in a non-standard way. Finally, we show that gamma-centroid (probabilistic) alignment can find highly reliable subsets of aligned bases.


CONCLUSIONS
These results enable more accurate genome alignment, with reliability measures for local alignments and for individual aligned bases. This study was made possible by our new software, LAST, which can align vertebrate genomes in a few hours http://last.cbrc.jp/.
Computational Biology Research Center, Institute for Advanced Industrial Science and Technology, Tokyo 135-0064, Japan. martin@cbrc.jp
Martin C
MC
Frith
Michiaki
M
Hamada
Paul
P
Horton
D001483:Base Sequence; D019295:Computational Biology / Q000379:methods; D016678:Genome; D008969:Molecular Sequence Data; D011506:Proteins / Q000737:chemistry; D012313:RNA / Q000737:chemistry; D016415:Sequence Alignment / Q000379:methods*; D017423:Sequence Analysis, RNA
D011506:Proteins; D012313:RNA