Online

A package to reconstruct species tree. MixTreEM uses a probabilistic generative mixture model to reconstruct a set of k-candidate species trees given a set of n monocopy gene families. In the first phase, a set of probable species trees are inferred given gene family data. In the second phase, each of the species tree, along with the gene families, is fed into DLRS (Duplication, Loss, Rate and Sequence) model, ultimately giving us the best species tree.

User report

×
Vote up tools and offer feedback
Give value to tools and make your expertise visible

0 user reviews

0 user reviews

No review has been posted.

MixTreEM forum

×
Communicate with other users
Participate in the forum to get support for using tools. Ask questions about technical specifications.

No open topic.

MixTreEM versioning

×
Upload and version your source code
Get your DOI for better tool traceability. Archive your releases so the community can easily visualize progress on you work.

No versioning.

MixTreEM classification

MixTreEM specifications

Software type:
Package/Module
Restrictions to use:
None
Output data:
Synthetic gene families as species tree
Programming languages:
C++
Computer skills:
Advanced
Maintained:
Yes
Interface:
Command line interface
Input data:
Gene families sequences
Operating system:
Unix/Linux, Windows
Parallelization:
MPI
Stability:
Stable
Source code URL:
http://prime.scilifelab.se/mixtreem/downloads/mixtreem_source.tar.gz

MixTreEM support

Maintainer

  • Jens Lagergren <>

Credits

×
Promote your skills
Define all the tasks you managed and assign your profile the appropriate badges. Become an active member.

Publications

Institution(s)

School of Computer Science and Communication, Science for Life Laboratory, KTH Royal Institute of Technology, Stockholm, Sweden; Department of Computer Science, Helsinki Institute for Information Technology HIIT, Aalto University, Espoo, Finland; School of Computer Science and Communication, Science for Life Laboratory, Swedish e-Science Research Center, KTH Royal Institute of Technology, Stockholm, Sweden

Funding source(s)

Swedish e-Science Research Center, The Swedish Research Council (2010-4757), University of Engineering and Technology, Peshawar, Pakistan and the Academy of Finland (Finnish Centre of Excellence in Computational Inference Research COIN, 251170)

Link to literature

By using OMICtools you acknowledge that you have read and accepted the terms of the end user license agreement.