RAxML vs. FastTree: A Comparison of Two Maximum Likelihood Phylogeny - - PowerPoint PPT Presentation

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RAxML vs. FastTree: A Comparison of Two Maximum Likelihood Phylogeny Estimation Methods Mia Schoening RAxML vs. FastTree RAxML FastTree Implements standard SPR-based Uses combination of Neighbor-Joining, hill-climbing

SLIDE 1

RAxML vs. FastTree: A Comparison of Two Maximum Likelihood Phylogeny Estimation Methods

Mia Schoening

SLIDE 2

RAxML vs. FastTree

RAxML

○ Implements standard SPR-based hill-climbing algorithm ○ Main method used for large-scale ML phylogeny estimation ○ Computational requirements limit number of sequences and sites

FastTree

○ Uses combination of Neighbor-Joining, Minimum Evolution, and ML-based NNI rearrangement methods ○ Can handle alignments up to 1 million sequences ○ On large alignments, orders of magnitude faster than RAxML and PhyML

SLIDE 3

RAxML vs. FastTree

RAxML

○ Implements standard SPR-based hill-climbing algorithm ○ Main method used for large-scale ML phylogeny estimation ○ Computational requirements limit number of sequences and sites

FastTree

○ Uses combination of Neighbor-Joining, Minimum Evolution, and ML-based NNI rearrangement methods ○ Can handle alignments up to 1 million sequences ○ On large alignments, orders of magnitude faster than RAxML and PhyML

When is it necessary to use RAxML over FastTree?

SLIDE 4

Model Tree

Sequence Type: DNA
Number of Sequences: 1001
Sequence Length: 5000 sites

SLIDE 5

Generating Model Tree Set

Branch Length

○ Small: x10 ○ Moderate: x50 ○ Large: x100

Number of Leaves

○ Dense: 1001 Taxa ○ Sparse: 50 Taxa

SLIDE 6

Generating Model Tree Set

Branch Length

○ Small: x10 ○ Moderate: x50 ○ Large: x100

Number of Leaves

○ Dense: 1001 Taxa ○ Sparse: 50 Taxa

1. Small-Sparse 2. Small-Dense 3. Moderate-Sparse 4. Moderate-Dense 5. Large-Sparse 6. Large-Dense

SLIDE 7

Software Versions

RAxML Version 8.2.12 FastTree Version 2.1.10

SLIDE 8

Running Time Analysis

SLIDE 9

ML Scores (as log likelihoods)

Small_Sparse Small_Dense Moderate_Sparse Moderate_Dense Large_Sparse Large_Dense

FastTree

210,099
3,387,957
242,980
4,324,461
253,999
4,571,306

RAxML

207,591
3,366,916
240,882
4,277,753
252,064
4,519,003

SLIDE 10

Tree Topology Analysis

SLIDE 11

Discussion

RAxML consistently outperforms FastTree with respect to ML scores and tree topology, but at the

cost of longer running times

Both methods had higher RF error values on sparse datasets than dense datasets
As edge lengths increased, RF error values increased for both methods

SLIDE 12

References

Liu K, Linder CR, Warnow T (2011) RAxML and FastTree: Comparing Two Methods for Large-Scale Maximum Likelihood Phylogeny Estimation. PLoS ONE 6(11): e27731. https://doi.org/10.1371/journal.pone.0027731 Price, M.N., Dehal, P.S., and Arkin, A.P. (2010) FastTree 2 -- Approximately Maximum-Likelihood Trees for Large Alignments. PLoS ONE, 5(3):e9490. doi:10.1371/journal.pone.0009490. Stamatakis, A. (2014) RAxML Version 8: A tool for Phylogenetic Analysis and Post-Analysis of Large

Phylogenies. Bioinformatics 30 (9): 1312-1313.

Xiaofan Zhou, Xing-Xing Shen, Chris Todd Hittinger, Antonis Rokas (2018) Evaluating Fast Maximum Likelihood-Based Phylogenetic Programs Using Empirical Phylogenomic Data Sets, Molecular Biology and Evolution, 35(2):486–503, https://doi.org/10.1093/molbev/msx302