MLGO: Maximum Likelihood for Gene Order Analysis (A Web Server)



MLGO is a web server designed for genome rearrangement and gene order analysis. It can be used to infer a phylogeny from genome rearrangement and gene order data, and can also obtain an estimation of ancestral genomes, given an input tree. It can handle large scale data with the size ranges from mitochandrial to nuclear genomes. Besides rearrangements, it can also handle gene insertion, deletion and duplication.

Tutorial

A simple tutorial is available from here.

Tools to prepare data and view results

You can also use the following tools to prepare gene order data, such as DRIMM, i-ADHoRe, Cyntenator. Biological datasets can be obtained from CoGE.

To view the resulted tree, you can use iTOL.

When you use this server, please provide a valid email so that results can be emailed to you. Sometime you may need to dig your spam folder as the email may be treated as spam by some mail providers.

If you need assistance, please email jtang at cse.sc.edu.

Input Data
Paste your gene orders
Must be in THIS format.
Click for a SAMPLE. (There are two more complex examples: one is available here, and the other is here.
or upload a data file
Maximum size is 5MB

Inference Settings
Inference Target

For Small Phylogeny Problem Only
Paste your phylogeny tree
Must be in Newick format
Click for a SAMPLE.
or upload a tree file
Maximum size is 1MB
Notification
Email


When publishing results obtained via the web-server please cite one from below:
Y. Lin, F. Hu, J. Tang and B. Moret
Maximum Likelihood Phylogenetic Reconstruction from High-Resolution Whole-Genome Data and a Tree of 68 Eukaryotes.
Pacific Symposium on Biocomputing 18:285-296(2013)
F. Hu, L. Zhou and J. Tang
Reconstructing Ancestral Genomic Orders Using Binary Encoding and Probabilistic Models.
Bioinformatics Research and Applications Lecture Notes in Computer Science Volume 7875, 2013, pp 17-27
F. Hu, J. Zhou and L. Zhou and J. Tang
Probabilistic Reconstruction of Ancestral Genomes with Gene Insertions and Deletions.
The Twelfth Asia Pacific Bioinformatics Conference, APBC 2014