1.1 Run PhylteR with Docker

PhylteR is available as a Docker container: https://hub.docker.com/r/treecoutheo/phylter_docker.

Here are the steps needed to use the docker version of phylter:

Warning: you may need administrator rights to use docker!

1. Pull the latest version of phylter container from the Docker Hub repository:

sudo docker pull treecoutheo/phylter_docker:latest

2. Run phylter on the example Carnivora dataset

sudo docker run -v $PWD:$PWD -w $PWD treecoutheo/phylter_docker phylter.py -j Carnivora_docker -t /usr/container-data/trees

• $PWD specifies that you work in your local Present Working Directory. This should not be changed.
• -j specifies the job name for this phylter run (and thus the name of the output folder)
• -t specifies the folder containing the input gene trees in Newick format (one tree per file)

The command above creates the directory Carnivora_docker that will contain:

• PhylteR_all_tree_named: a single file containing all the trees with the gene ID preceding the newick.
• phylter.out: the phylter output file containing the log of the run and the list of identified outliers.

3. Run phylter on the example Carnivora dataset AND prune trees AND remove outliers from fasta files

You may want to run phylter and to subsequently remove the identified outliers from both the gene trees and the sequences files. For this to be performed, the sequence files must contain the same name as the corresponding tree, minus the extension if any. For example, a sequence file named ENSG00000274286_ADRA2B_final_align_NT.aln will be matched automatically to a tree file named ENSG00000274286_ADRA2B.treefile: phylter.py will identify the gene ID as being ENSG00000274286_ADRA2B.

sudo docker run -v $PWD:$PWD -w $PWD treecoutheo/phylter_docker phylter.py -j Carnivora_docker -t /usr/container-data/trees -p TRUE -s /usr/container-data/alignments -g TRUE

• -p TRUE specifies that the input trees should be pruned by removing the outliers identified by phylter. A new directorry containing the pruned trees is created (see after).
• -s specifies the directory containing the sequences (see above for specifications regarding naming conventions). If this directory is specified, the input sequences will be filtered by removing the outliers identified by phylter. A new directorry containing the filtered sequences is created (see after).
• -g TRUE specifies that a full report (in pdf) should be produced (in addition to the default phylter.out file).

The command above generates, in addition to the two files described in the previous example:

• Carnivora_docker/trees_PhylteR/: a directory containing the trees pruned from their outliers. Note that the number of trees inside the directory can be lower than the number of trees used as input in case all species from a gene tree have been identified as outliers.

• Carnivora_docker/seqs_PhylteR/: a directory containing sequences with outlier sequences filtered out. The number of sequences files inside the directory can be lower than the number of sequences files used as input. Again, the number of sequence files inside the directory can be lower than the number of trees sequence files in the input directory in case all species from a gene tree have been identified as outliers.

• report.pdf: a PDF report containing a summary of the results.

4. Prune trees and filter out sequences AFTER the phylter run.

Instead of performing the phylter analysis and the filtering of outliers at the same time, you can do it in multiple steps. here is how, on the example dataset:

• Run phylter:

sudo docker run -v $PWD:$PWD -w $PWD treecoutheo/phylter_docker phylter.py -j Carnivora_docker -t /usr/container-data/trees

The output file phylter.out will be used for performing the pruning and/or the sequence filtering (see below).

• Prune trees with prune_tree_outliers.R:

sudo docker run -v $PWD:$PWD -w $PWD treecoutheo/phylter_docker prune_tree_outliers.R container-data_phylter /usr/container-data/trees Carnivora_docker/phylter.out

• Filter alignments with remove_sequence_outliers.py:

sudo docker run -v $PWD:$PWD -w $PWD treecoutheo/phylter_docker remove_sequence_outliers.py -j container-data_phylter -s /usr/container-data/alignments -o Carnivora_docker/phylter.out

5. View all phylter options

phylter.py allows specifying all the options available in the R package. To see this list of options, simply use the -h option:

sudo docker run -v $PWD:$PWD -w $PWD treecoutheo/phylter_docker phylter.py -h

1.2 Run PhylteR with Singularity

PhylteR is also available as a singularity container : (https://cloud.sylabs.io/library/theo.treecou/tool/phylter_singularity). Here are instructions to install (or build) and run it:

1. Pull the latest version of phylter container from the Sylabs repository:

sudo singularity pull PhylteR.sif library://theo.treecou/tool/phylter_singularity:latest

Alternatively, you can build a singularity image from the Docker Hub repository:

sudo singularity pull PhylteR.sif docker://treecoutheo/phylter_docker:latest

2.a Run phylter on the carnivora example dataset:

singularity exec -B $PWD PhylteR.sif phylter.py -j Carnivora_singularity -t /usr/container-data/trees

Note: For more options Please, refer to the description of the docker container to see how to use all the options available with the phylter.py function.

2.b Alternatively, you can open a console in the singularity container as follows and use R in that console:

singularity shell -B $PWD PhylteR.sif

R # this launch the version of R from inside the singularity

Then:

library(phylter)

list_trees <- Sys.glob("/usr/container-data/trees/ENSG*.treefile")

trees <- lapply(list_trees, ape::read.tree)

results <- phylter(trees, parallel = FALSE)