ERATE 0.8 – Maximum Likelihood Phylogenetic Inference

ERATE 0.8

:: DESCRIPTION

erate is an extension of Joe Felsenstein’s DNAML program which treats insertions and deletions as evolutionary events, rather than ignoring them as missing data (which is what the most widely used phylogenetic inference programs all do).

::DEVELOPER

Elena Rivas, Eddy lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

ERATE

:: MORE INFORMATION

Citation

Probabilistic Phylogenetic Inference with Insertions and Deletions.
E. Rivas, S. R. Eddy.
PLoS Comput. Biol., 4:e1000172, 2008.

LAPD – Estimate Maximum Likelihood Allele and two-locus Haplotype Frequencies

LAPD

:: DESCRIPTION

LAPD (Linkage Analysis Using Pedigree Data) allows to estimate maximum likelihood allele and two-locus haplotype frequencies, using an Expectation-Maximization algorithm, taking into account family relationships of the individuals.

::DEVELOPER

Computational and Molecular Population Genetics Lab, University of Bern

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows

:: DOWNLOAD

LAPD

:: MORE INFORMATION

Citation

Excoffier, L. and Slatkin, M. (1998)
Incorporating genotypes of relatives into a test of linkage disequilibrium,
Am. J. Hum. Genet. 162:171-180.

MACML 1.1.2 – Model Averaging Clustering by Maximum Likelihood

MACML 1.1.2

:: DESCRIPTION

MACML is a program that clusters sequences into heterogeneous regions with specific site types, without requiring any prior knowledge.

::DEVELOPER

the Townsend Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Linux / MacOsX
C++Compiler

:: DOWNLOAD

MACML

:: MORE INFORMATION

Citation

PLoS Comput Biol. 2009 Jun;5(6):e1000421. Epub 2009 Jun 26.
Maximum-likelihood model averaging to profile clustering of site types across discrete linear sequences.
Zhang Z, Townsend JP.

SILP2 – ILP-based Maximum Likelihood Genome Scaffolding

SILP2

:: DESCRIPTION

SILP2 is a stand-alone scaffolding tool that generates maximum likelihood scaffolds via integer linear programming (ILP). SILP2 achieves high scalability without sacrificing optimality by solving the large ILP formulations required to scaffold mammalian-size genomes via a non-serial dynamic programming (NSDP) approach based on decomposing the scaffolding graph into 3-connected components.

::DEVELOPER

Bioinformatics Lab , Computer Science & Engineering Dept. University of Connecticut

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

SILP2

:: MORE INFORMATION

Citation:

BMC Bioinformatics. 2014;15 Suppl 9:S9. doi: 10.1186/1471-2105-15-S9-S9. Epub 2014 Sep 10.
ILP-based maximum likelihood genome scaffolding.
Lindsay J, Salooti H, Măndoiu I, Zelikovsky A.

STEM 2.0 / STEM-hy 1.0 – Species Tree Estimation using Maximum likelihood (with hybridization)

STEM 2.0 / STEM-hy 1.0

:: DESCRIPTION

STEM-hy is a program for inferring maximum likelihood species trees from a collection of estimated gene trees under the coalescent model

::DEVELOPER

Laura S. Kubatko

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Windows/ MacOsX
Java

:: DOWNLOAD

STEM / STEM-hy

:: MORE INFORMATION

Citation

Kubatko, L., B. C. Carstens, and L. L. Knowles. 2009.
STEM: Species Tree Estimation using Maximum likelihood for gene trees under coalescence,
Bioinformatics (2009) 25 (7): 971-973.doi: 10.1093/bioinformatics/btp079

SSA 1.0 – Inference of Maximum Likelihood Phylogenetic Trees Using a Stochastic Search Algorithm

SSA 1.0

:: DESCRIPTION

SSA is a program for inferring maximum likelihood phylogenies from DNA sequences. Two versions of the program are available: one which assumes a molecular clock and one which does not make this assumption. The method for searching the space of trees for the ML tree is based on a simulated-annealing type algorithm and is described in the reference above. The program implements Felsenstein’s F84 model of nucleotide substitution and associated sub-models. The program estimates the ML tree and branch lengths, and can optionally estimate the transversion/transversion ratio. Upon termination, the program returns the k trees of highest likelihood found during the search, where k can be set by the user.

::DEVELOPER

Laura S. Kubatko

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux/ Windows

:: DOWNLOAD

SSA

:: MORE INFORMATION

Citation

Salter, L. and D. Pearl. 2001.
Stochastic Search Strategy for Estimation of Maximum Likelihood Phylogenetic Trees,
Systematic Biology 50(1): 7-17.

SSAMK – Inference of Maximum Likelihood Phylogenetic Trees for Morphological Data

SSAMK

:: DESCRIPTION

SSAMK uses a stochastic search algorithm for estimation of maximum likelihood phylogenetic trees for morphological data

::DEVELOPER

Laura S. Kubatko

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux

:: DOWNLOAD

SSAMK

:: MORE INFORMATION

Citation

Syst Biol. 2001 Nov-Dec;50(6):913-25.
A likelihood approach to estimating phylogeny from discrete morphological character data.
Lewis PO.

GeneRax 1.0.0 – Maximum Likelihood based Gene Tree Inference

GeneRax 1.0.0

:: DESCRIPTION

GeneRax is a tool for species tree-aware maximum likelihood based gene tree inference under gene duplication, transfer, and loss.

::DEVELOPER

the Exelixis Lab

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Linux / MacOs

:: DOWNLOAD

GeneRax

:: MORE INFORMATION

Citation

Benoit Morel, Alexey M. Kozlov, Alexandros Stamatakis, Gergely Szöllősi.
GeneRax: A tool for species tree-aware maximum likelihood based gene tree inference under gene duplication, transfer, and loss.
bioRxiv, 779066, 2019

RAxML 8.2.12 / RAxML-NG 0.9.0- Sequential and Parallel Maximum Likelihood based inference of large phylogenetic trees

RAxML 8.2.12 / RAxML-NG 0.9.0

:: DESCRIPTION

RAxML (Randomized Axelerated Maximum Likelihood) is a program for sequential and parallel Maximum Likelihood based inference of large phylogenetic trees. It has originally been derived from fastDNAml which in turn was derived from Joe Felsentein’s dnaml which is part of the PHYLIP package.

RAxML-NG is a phylogenetic tree inference tool which uses maximum-likelihood (ML) optimality criterion. Its search heuristic is based on iteratively performing a series of Subtree Pruning and Regrafting (SPR) moves, which allows to quickly navigate to the best-known ML tree. RAxML-NG is a successor of RAxML (Stamatakis 2014) and leverages the highly optimized likelihood computation implemented in libpll (Flouri et al. 2014).

::DEVELOPER

the Exelixis Lab

:: SCREENSHOTS

:: REQUIREMENTS

Linux / Windows / MacOsX
Java

:: DOWNLOAD

RAxML , RAxML-NG

:: MORE INFORMATION

Citation

Bioinformatics. 2019 Nov 1;35(21):4453-4455. doi: 10.1093/bioinformatics/btz305.
RAxML-NG: a fast, scalable and user-friendly tool for maximum likelihood phylogenetic inference.
Kozlov AM, Darriba D, Flouri T, Morel B, Stamatakis A

Bioinformatics. 2014 May 1;30(9):1312-3. doi: 10.1093/bioinformatics/btu033. Epub 2014 Jan 21.
RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies.
Stamatakis A.

S.A. Berger, D. Krompaß, A. Stamatakis:
“Performance, Accuracy and Web-Server for Evolutionary Placement of Short Sequence Reads under maximum-likelihood“.
Systematic Biology 60(3):291-302, 2011.

tree-puzzle 5.3.rc16 – Maximum Likelihood Analysis

tree-puzzle 5.3.rc16

:: DESCRIPTION

TREE-PUZZLE is a computer program to reconstruct phylogenetic trees from molecular sequence data by maximum likelihood. It implements a fast tree search algorithm, quartet puzzling, that allows analysis of large data sets and automatically assigns estimations of support to each internal branch. TREEPUZZLE also computes pairwise maximum likelihood distances as well as branch lengths for user specified trees. Branch lengths can be calculated with and without the molecular-clock assumption. In addition, TREE-PUZZLE o ers likelihood mapping, a method to investigate the support of a hypothesized internal branch without computing an overall tree and to visualize the phylogenetic content of a sequence alignment. TREE-PUZZLE also conducts a number of statistical tests on the data set (chi-square test for homogeneity of base composition, likelihood ratio to test the clock hypothesis, one and two-sided Kishino-Hasegawa test, Shimodaira-Hasegawa test, Expected Likelihood Weights). The models of substitution provided by TREE-PUZZLE are GTR, TN, HKY, F84, SH for nucleotides, Dayhoff, JTT, mtREV24, BLOSUM 62, VT, WAG for amino acids, and F81 for two-state data. Rate heterogeneity is modeled by a discrete Gamma distribution and by allowing invariable sites. The corresponding parameters (except for GTR) can be inferred from the data set.

::DEVELOPER

Heiko A. Schmidt & Arndt von Haeseler

:: SCREENSHOTS

N/A

:: REQUIREMENTS

Windows / Linux / MacOSX

:: DOWNLOAD

tree-puzzle

:: MORE INFORMATION

Citation

Schmidt, H.A., K. Strimmer, M. Vingron, and A. von Haeseler (2002)
TREE-PUZZLE: maximum likelihood phylogenetic analysis using quartets and parallel computing.
Bioinformatics. 18:502-504.