pegi3s/iqtree3 repository overview

⁠This image belongs to a larger project called Bioinformatics Docker Images Project (http://pegi3s.github.io/dockerfiles⁠)

⁠(Please note that the original software licenses still apply)

This image facilitates the usage of IQ-TREE 3⁠, IQ-TREE 3 is a fast and versatile phylogenetic inference software that performs maximum-likelihood tree reconstruction, automatic evolutionary model selection, branch support analysis, partitioned phylogenomic analyses, ancestral state reconstruction, topology tests, and several other downstream phylogenetic tasks.

⁠Using the IQ-TREE 3 image in Linux

You should adapt and run the following command: docker run --rm -v /your/data/dir:/data pegi3s/iqtree3 iqtree3 -s /data/your_alignment.fasta -m MFP -mtree --merit BIC -B 1000 -alrt 1000 --bnni --seed 1 --prefix /data/output_files/run1 -T AUTO

In this command, you should replace:

• /your/data/dir with your actual working directory
• your_alignment.fasta with the actual name of your alignment file inside your working directory
• output_files with the actual name of the folder where you want the output files to be written
• run1 with the prefix you want for the output files

NOTES:

• The output folder must already exist before running the command
• This command is a robust default setup that performs automatic model selection, tree inference, and branch support analysis. See the manual for details.

⁠Options used in the standard command

• -m MFP: perform extended ModelFinder model selection and then infer the tree under the best-fit model
• -mtree: perform a full tree search for every tested model during model selection
• --merit BIC: use BIC as the criterion to rank and choose the best model
• -B 1000: perform 1000 ultrafast bootstrap replicates
• -alrt 1000: perform 1000 SH-aLRT replicates
• --bnni: optimize bootstrap trees by NNI on bootstrap alignments to reduce inflated support values
• --seed 1: set a fixed random seed for reproducibility
• --prefix /data/output_files/run1: prefix for all output files
• -T AUTO: automatically detect and use the available CPU threads

⁠Other useful options

• --seqtype <type>: explicitly set the sequence type (BIN, DNA, AA, NT2AA, CODON, MORPH)
• -t <file|PARS|RAND>: specify a starting tree
• -o <taxon[,taxon,...]>: define outgroup taxon or taxa
• -p <file>: partition file for partitioned analyses
• --redo: redo both ModelFinder and tree search
• --redo-tree: keep ModelFinder result and redo only the tree search
• --safe: enable safe likelihood kernel to avoid numerical underflow
• --mem <num[G|M|%]>: limit RAM usage
• --runs <num>: number of independent runs
• -v: verbose mode
• -h: print the help text
• -V: show the current version number

⁠Additional usage examples

⁠Model selection only

docker run --rm -v /your/data/dir:/data pegi3s/iqtree3 iqtree3 -s /data/your_alignment.fasta -m MF -mtree --merit BIC --prefix /data/output_files/modeltest -T AUTO

⁠Use a fixed model instead of automatic model selection

docker run --rm -v /your/data/dir:/data pegi3s/iqtree3 iqtree3 -s /data/your_alignment.fasta -m GTR+F+I+G4 --prefix /data/output_files/run1 -T AUTO

⁠Partitioned analysis

docker run --rm -v /your/data/dir:/data pegi3s/iqtree3 iqtree3 -s /data/concat_alignment.fasta -p /data/partitions.nex -m MFP+MERGE --merit BIC -B 1000 --seed 1 --prefix /data/output_files/run1 -T AUTO

⁠Additional remarks

• A single alignment usually means one alignment analyzed under one overall model
• A partitioned phylogenomic analysis usually means a concatenated alignment split into multiple partitions, such as genes or codon positions
• For partitioned datasets, using -p with a partition file is generally more appropriate than treating the whole matrix as a single alignment
• If you want to inspect the ranking of tested models, check the .model.gz file
• If you want to inspect the final chosen model and fitted parameters, check the .iqtree file

To see the IQ-TREE 3⁠ help, just run: docker run --rm pegi3s/iqtree3 iqtree3 -h