readIgphyml {alakazam}R Documentation

Read in output from IgPhyML

Description

readIgphyml reads output from the IgPhyML phylogenetics inference package for B cell repertoires

Usage

readIgphyml(
  file,
  id = NULL,
  format = c("graph", "phylo"),
  collapse = FALSE,
  branches = c("mutations", "distance")
)

Arguments

file

IgPhyML output file (.tab).

id

ID to assign to output object.

format

if "graph" return trees as igraph graph objects. if "phylo" return trees as ape phylo objects.

collapse

if TRUE transform branch lengths to units of substitutions, rather than substitutions per site, and collapse internal nodes separated by branches < 0.1 substitutions. Will also remove all internal node labels, as it makes them inconsistent.

branches

if "distance" branch lengths are in expected mutations per site. If "mutations" branches are in expected mutations.

Details

readIgphyml reads output from the IgPhyML repertoire phylogenetics inference package. The resulting object is divded between parameter estimates (usually under the HLP19 model), which provide information about mutation and selection pressure operating on the sequences.

Trees returned from this function are either igraph objects or phylo objects, and each may be visualized accordingly. Futher, branch lengths in tree may represent either the expected number of substitutions per site (codon, if estimated under HLP or GY94 models), or the total number of expected substitutions per site. If the latter, internal nodes - but not tips - separated by branch lengths less than 0.1 are collapsed to simplify viewing.

Value

A list containing IgPhyML model parameters and estimated lineage trees.

Object attributes:

References

  1. Hoehn KB, Lunter G, Pybus OG - A Phylogenetic Codon Substitution Model for Antibody Lineages. Genetics 2017 206(1):417-427 https://doi.org/10.1534/genetics.116.196303

  2. Hoehn KB, Vander Heiden JA, Zhou JQ, Lunter G, Pybus OG, Kleinstein SHK - Repertoire-wide phylogenetic models of B cell molecular evolution reveal evolutionary signatures of aging and vaccination. bioRxiv 2019 https://doi.org/10.1101/558825

Examples

## Not run: 
   # Read in and plot a tree from an igphyml run
   library(igraph)
   s1 <- readIgphyml("IB+7d_lineages_gy.tsv_igphyml_stats_hlp.tab", id="+7d")
   print(s1$param$OMEGA_CDR_MLE[1])
   plot(s1$trees[[1]], layout=layout_as_tree, edge.label=E(s1$trees[[1]])$weight)

## End(Not run)


[Package alakazam version 1.1.0 Index]