Quick start

IgPhyML is easiest to use when run indirectly through the Change-O program BuildTrees by specifying the --igphyml option. Most of these instructions require Change-O 0.4.6 or higher, Alakazam 0.3.0 or higher, and IgPhyML to be installed, with the executable in your PATH variable. If these aren’t possible, see IgPhyML standalone operation

To view all options for BuildTrees , run the command:

BuildTrees.py --help

The following commands should work as a first pass on many reasonably sized datasets, but if you really want to understand what’s going on or make sure what you’re doing makes sense, please check out the rest of the website.

Build trees and estimate model parameters

Move to the examples subfolder and run:

BuildTrees.py -d example.tab --outname ex --log ex.log --collapse \
    --sample 3000 --igphyml --clean all --nproc 1

This command processes an AIRR-formatted dataset of BCR sequences that have been clonally clustered with germlines reconstructed. It then quickly builds trees using the GY94 model and, using these fixed topologies, estimates HLP19 model parameters. This can be sped up by increasing the --nproc option. Subsampling using the --sample option in isn’t strictly necessary, but IgPhyML will run slowly when applied to large datasets. Here, the --collapse flag is used to collapse identical sequences. This is highly recommended because identical sequences slow down calculations without affecting likelihood values in IgPhyML.

Visualize results

The output file of the above command can be read using the readIgphyml function of Alakazam. After opening an R session, enter the following commands. Note that when using the Docker container, you’ll need to run dev.off() after plotting the tree to create a pdf plot in the examples directory:


db = readIgphyml("ex_igphyml-pass.tab")

#plot largest lineage tree

#show HLP10 parameters
NSEQ          "4"
NSITE         "107"
TREE_LENGTH   "0.286"
LHOOD         "-290.7928"
KAPPA_MLE     "2.266"
OMEGA_FWR_MLE "0.5284"
OMEGA_CDR_MLE "2.3324"
WRC_2_MLE     "4.8019"
GYW_0_MLE     "3.4464"
WA_1_MLE      "5.972"
TW_0_MLE      "0.8131"
SYC_2_MLE     "-0.99"
GRS_0_MLE     "0.2583"
map to buried treasure

Lineage tree of example clone.