TY - GEN
T1 - Phylogenetic reconstruction from arbitrary gene-order data
AU - Tang, Jijun
AU - Moret, Bernard M.E.
AU - Cui, Liying
AU - DePamphilis, Claude W.
PY - 2004
Y1 - 2004
N2 - Phylogenetic reconstruction from gene-order data has attracted attention from both biologists and computer scientists over the last few years. So far, our software suite GRAPPA is the most accurate approach, but it requires that all genomes have identical gene content, with each gene appearing exactly once in each genome. Some progress has been made in handling genomes with unequal gene content, both in terms of computing pairwise genomic distances and in terms of reconstruction. In this paper, we present a new approach for computing the median of three arbitrary genomes and apply it to the reconstruction of phytogenies from arbitrary gene-order data. We implemented these methods within GRAPPA and tested them on simulated datasets under various conditions as well as on a real dataset of chloroplast genomes; we report the results of our simulations and our analysis of the real dataset and compare them to reconstructions made by using neighbor-joining and using the original GRAPPA on the same genomes with equalized gene contents. Our new approach is remarkably accurate both in simulations and on the real dataset, in contrast to the distance-based approaches and to reconstructions using the original GRAPPA applied to equalized gene contents.
AB - Phylogenetic reconstruction from gene-order data has attracted attention from both biologists and computer scientists over the last few years. So far, our software suite GRAPPA is the most accurate approach, but it requires that all genomes have identical gene content, with each gene appearing exactly once in each genome. Some progress has been made in handling genomes with unequal gene content, both in terms of computing pairwise genomic distances and in terms of reconstruction. In this paper, we present a new approach for computing the median of three arbitrary genomes and apply it to the reconstruction of phytogenies from arbitrary gene-order data. We implemented these methods within GRAPPA and tested them on simulated datasets under various conditions as well as on a real dataset of chloroplast genomes; we report the results of our simulations and our analysis of the real dataset and compare them to reconstructions made by using neighbor-joining and using the original GRAPPA on the same genomes with equalized gene contents. Our new approach is remarkably accurate both in simulations and on the real dataset, in contrast to the distance-based approaches and to reconstructions using the original GRAPPA applied to equalized gene contents.
UR - http://www.scopus.com/inward/record.url?scp=4544340629&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=4544340629&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:4544340629
SN - 0769521738
T3 - Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004
SP - 592
EP - 599
BT - Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004
T2 - Proceedings - Fourth IEEE Symposium on Bioinformatics and Bioengineering, BIBE 2004
Y2 - 19 May 2004 through 21 May 2004
ER -