shmulateTree {shazam}

Simulate mutations in a lineage tree

Description

shmulateTree returns a set of simulated sequences generated from an input sequence and a lineage tree. The input sequence is used to replace the most recent common ancestor (MRCA) node of the igraph object defining the lineage tree. Sequences are then simulated with mutations corresponding to edge weights in the tree. Sequences will not be generated for groups of nodes that are specified to be excluded.

Usage

shmulateTree(
  sequence,
  graph,
  targetingModel = HH_S5F,
  field = NULL,
  exclude = NULL,
  junctionWeight = NULL,
  start = 1,
  end = nchar(sequence)
)

Arguments

sequence

string defining the MRCA sequence to seed mutations from.

graph

igraph object defining the seed lineage tree, with vertex annotations, whose edges are to be recreated.

targetingModel

5-mer TargetingModel object to be used for computing probabilities of mutations at each position. Defaults to HH_S5F.

field

annotation to use for both unweighted path length exclusion and consideration as the MRCA node. If NULL do not exclude any nodes.

exclude

vector of annotation values in field to exclude from potential MRCA set. If NULL do not exclude any nodes. Has no effect if field=NULL.

junctionWeight

fraction of the nucleotide sequence that is within the junction region. When specified this adds a proportional number of mutations to the immediate offspring nodes of the MRCA. Requires a value between 0 and 1. If NULL then edge weights are unmodified from the input graph.

start

Initial position in sequence where mutations can be introduced. Default: 1

end

Last position in sequence where mutations can be introduced. Default: last position (sequence length).

Value

A data.frame of simulated sequences with columns:

• name: name of the corresponding node in the input graph.

• sequence: mutated sequence.

• distance: Hamming distance of the mutated sequence from the seed sequence.

See Also

See shmulateSeq for imposing mutations on a single sequence. See HH_S5F and MK_RS5NF for predefined TargetingModel objects.

Examples

# Load example lineage and define example MRCA
data(ExampleTrees, package="alakazam")
graph <- ExampleTrees[[17]]
sequence <- "NGATCTGACGACACGGCCGTGTATTACTGTGCGAGAGATAGTTTA"

# Simulate using the default human 5-mer targeting model
shmulateTree(sequence, graph)

# Simulate using the mouse 5-mer targeting model
# Exclude nodes without a sample identifier
# Add 20% mutation rate to the immediate offsprings of the MRCA
shmulateTree(sequence, graph, targetingModel=MK_RS5NF,
             field="sample_id", exclude=NA, junctionWeight=0.2)