shazam (version 1.2.0)

createTargetingMatrix: Calculates a targeting rate matrix

Description

createTargetingMatrix calculates the targeting model matrix as the combined probability of mutability and substitution.

Usage

createTargetingMatrix(substitutionModel, mutabilityModel)

Value

A TargetingMatrix with the same dimensions as the input substitutionModel

containing normalized targeting probabilities for each 5-mer motif with row names defining the center nucleotide and column names defining the 5-mer nucleotide sequence.

If the input mutabilityModel is of class MutabilityModel, then the output

TargetingMatrix will carry over the input numMutS and numMutR slots.

Arguments

substitutionModel

matrix of 5-mers substitution rates built by createSubstitutionMatrix or extendSubstitutionMatrix.

mutabilityModel

vector of 5-mers mutability rates built by createMutabilityMatrix or extendMutabilityMatrix.

Details

Targeting rates are calculated by multiplying the normalized mutability rate by the normalized substitution rates for each individual 5-mer.

References

1. Yaari G, et al. Models of somatic hypermutation targeting and substitution based on synonymous mutations from high-throughput immunoglobulin sequencing data. Front Immunol. 2013 4(November):358.

See Also

createSubstitutionMatrix, extendSubstitutionMatrix, createMutabilityMatrix, extendMutabilityMatrix, TargetingMatrix, createTargetingModel

Examples

# \donttest{
# Subset example data to 50 sequences, of one isotype and sample as a demo
data(ExampleDb, package="alakazam")
db <- subset(ExampleDb, c_call == "IGHA" & sample_id == "-1h")[1:50,]

# Create 4x1024 models using only silent mutations
sub_model <- createSubstitutionMatrix(db, model="s", sequenceColumn="sequence_alignment",
                                      germlineColumn="germline_alignment_d_mask",
                                      vCallColumn="v_call")
mut_model <- createMutabilityMatrix(db, sub_model, model="s",
                                    sequenceColumn="sequence_alignment",
                                    germlineColumn="germline_alignment_d_mask",
                                    vCallColumn="v_call")

# Extend substitution and mutability to including Ns (5x3125 model)
sub_model <- extendSubstitutionMatrix(sub_model)
mut_model <- extendMutabilityMatrix(mut_model)

# Create targeting model from substitution and mutability
tar_model <- createTargetingMatrix(sub_model, mut_model)
# }