createTargetingModel - Creates a TargetingModel
createTargetingModel creates a 5-mer
createTargetingModel(db, model = c("RS", "S"), sequenceColumn = "SEQUENCE_IMGT", germlineColumn = "GERMLINE_IMGT_D_MASK", vCallColumn = "V_CALL", multipleMutation = c("independent", "ignore"), minNumMutations = 50, minNumSeqMutations = 500, modelName = "", modelDescription = "", modelSpecies = "", modelCitation = "", modelDate = NULL)
- data.frame containing sequence data.
- type of model to create. The default model, “RS”, creates a model by counting both replacement and silent mutations. The “S” specification builds a model by counting only silent mutations.
- name of the column containing IMGT-gapped sample sequences.
- name of the column containing IMGT-gapped germline sequences.
- name of the column containing the V-segment allele calls.
- string specifying how to handle multiple mutations occuring
within the same 5-mer. If
"independent"then multiple mutations within the same 5-mer are counted indepedently. If
"ignore"then 5-mers with multiple mutations are excluded from the otal mutation tally.
- minimum number of mutations required to compute the 5-mer substitution rates. If the number of mutations for a 5-mer is below this threshold, its substitution rates will be estimated from neighboring 5-mers. Default is 50.
- minimum number of mutations in sequences containing each 5-mer to compute the mutability rates. If the number is smaller than this threshold, the mutability for the 5-mer will be inferred. Default is 500.
- name of the model.
- description of the model and its source data.
- genus and species of the source sequencing data.
- publication source.
- date the model was built. If
NULLthe current date will be used.
A TargetingModel object.
- 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.
# Subset example data to one isotype and sample as a demo data(ExampleDb, package="alakazam") db <- subset(ExampleDb, ISOTYPE == "IgA" & SAMPLE == "-1h") # Create model using only silent mutations and ignore multiple mutations model <- createTargetingModel(db, model="S", multipleMutation="ignore")
Warning:Insufficient number of mutations to infer some 5-mers. Filled with 0.
See TargetingModel for the return object. See plotMutability plotting a mutability model. See createSubstitutionMatrix, extendSubstitutionMatrix, createMutabilityMatrix, extendMutabilityMatrix and createTargetingMatrix for component steps in building a model.