Immunoglobulin Somatic Hypermutation Analysis
S4 class defining a BASELINe (selection) object
Calculate the BASELINe PDFs (including for regions that include CDR3 a...
Calculate expected mutation frequencies of a sequence
Count the number of observed mutations in a sequence.
Calculates a 5-mer distance matrix from a TargetingModel object
Calculate total mutability
Constructs effective clonal sequences for all clones
Construct a consensus sequence
convertNumbering: IMGT-Kabat number conversion
Creates a Baseline object
Builds a mutability model
Creates a MutationDefinition
Creates a RegionDefinition
Builds a substitution model
Calculates a targeting rate matrix
Creates a TargetingModel
Output of the dens
method of findThreshold
Distance to nearest neighbor
Edit the Baseline object
Calculate expected mutation frequencies
Extends a mutability model to include Ns.
Extends a substitution model to include Ns.
Find distance threshold
Output of the gmm
method of findThreshold
Group BASELINe PDFs
IMGT unique numbering schemes
Make a 1-mer mutability model by averaging over a 5-mer mutability mod...
Make a 1-mer substitution model by averaging over a 5-mer substitution...
Make a degenerate 5-mer mutability model based on a 1-mer mutability m...
Make a degenerate 5-mer substitution model based on a 1-mer substituti...
Build a data.frame from a ChangeoClone and an igraph object containing...
Parameter tuning for minNumMutations
Parameter tuning for minNumSeqMutations
S4 class defining a mutability model
Amino acid mutation definitions
S4 class defining replacement and silent mutation definitions
Calculate observed numbers of mutations
Plots BASELINe probability density functions
Plots BASELINe summary statistics
Plot findThreshold results for the density method
Plot findThreshold results for the gmm method
Plot mutability probabilities
Visualize parameter tuning for sliding window approach
Visualize parameter tuning for minNumMutations and minNumSeqMutations
S4 class defining a region definition
Build a RegionDefinition object that includes CDR3 and FWR4.
shazam: Immunoglobulin Somatic Hypermutation Analysis
The shazam package
Simulate mutations in a single sequence
Simulate mutations in a lineage tree
Sliding window approach towards filtering sequences in a data.frame
Sliding window approach towards filtering a single sequence
Parameter tuning for sliding window approach
slideWindowTunePlot - plotSlideWindowTune backward compatability
Calculate BASELINe summary statistics
S4 class defining a targeting matrix
S4 class defining a targeting model
Two-sided test of BASELINe PDFs
Write targeting model distances to a file
Provides a computational framework for analyzing mutations in immunoglobulin (Ig) sequences. Includes methods for Bayesian estimation of antigen-driven selection pressure, mutational load quantification, building of somatic hypermutation (SHM) models, and model-dependent distance calculations. Also includes empirically derived models of SHM for both mice and humans. Citations: Gupta and Vander Heiden, et al (2015) <doi:10.1093/bioinformatics/btv359>, Yaari, et al (2012) <doi:10.1093/nar/gks457>, Yaari, et al (2013) <doi:10.3389/fimmu.2013.00358>, Cui, et al (2016) <doi:10.4049/jimmunol.1502263>.