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SHazaM

SHazaM is part of the Immcantation analysis framework for Adaptive Immune Receptor Repertoire sequencing (AIRR-seq) and provides tools for advanced analysis of somatic hypermutation (SHM) in immunoglobulin (Ig) sequences. Shazam focuses on the following
analysis topics:

  1. Quantification of mutational load
    SHazaM includes methods for determine the rate of observed and expected mutations under various criteria. Mutational profiling criteria include rates under SHM targeting models, mutations specific to CDR and FWR regions, and physicochemical property dependent substitution rates.
  2. Statistical models of SHM targeting patterns
    Models of SHM may be divided into two independent components: (a) a mutability model that defines where mutations occur and (b) a nucleotide substitution model that defines the resulting mutation. Collectively these two components define an SHM targeting model. SHazaM provides empirically derived SHM 5-mer context mutation models for both humans and mice, as well tools to build SHM targeting models from data.
  3. Analysis of selection pressure using BASELINe
    The Bayesian Estimation of Antigen-driven Selection in Ig Sequences (BASELINe) method is a novel method for quantifying antigen-driven selection in high-throughput Ig sequence data. BASELINe uses SHM targeting models can be used to estimate the null distribution of expected mutation frequencies, and provide measures of selection pressure informed by known AID targeting biases.
  4. Model-dependent distance calculations
    SHazaM provides methods to compute evolutionary distances between sequences or set of sequences based on SHM targeting models. This information is particularly useful in understanding and defining clonal relationships.

Contact

For help and questions please contact the Immcantation Group or use the issue tracker.

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Version

Install

install.packages('shazam')

Monthly Downloads

608

Version

0.1.9

License

CC BY-SA 4.0

Maintainer

Jason Vander Heiden

Last Published

March 31st, 2018

Functions in shazam (0.1.9)

MK_RS1NF

Mouse kappa chain, replacement and silent, 1-mer, non-functional substitution model.
GmmThreshold-class

Output of the gmm method of findThreshold
U5N

Uniform 5-mer null targeting model.
calcExpectedMutations

Calculate expected mutation frequencies of a sequence
HH_S1F

Human heavy chain, silent, 1-mer, functional substitution model.
calcBaseline

Calculate the BASELINe PDFs
calcObservedMutations

Count the number of observed mutations in a sequence.
createSubstitutionMatrix

Builds a substitution model
createTargetingMatrix

Calculates a targeting rate matrix
getnproc

Determines the numbers of CPU cores available
createTargetingModel

Creates a TargetingModel
HKL_S5F

Human kappa and lambda light chain, silent, 5-mer, functional targeting model.
IMGT_SCHEMES

IMGT unique numbering schemes
calcTargetingDistance

Calculates a 5-mer distance matrix from a TargetingModel object
Baseline-class

S4 class defining a BASELINe (selection) object
calculateMutability

Calculate total mutability
distToNearest

Distance to nearest neighbor
groupBaseline

Group BASELINe PDFs
MUTATION_SCHEMES

Amino acid mutation definitions
createBaseline

Creates a Baseline object
extendMutabilityMatrix

Extends a mutability model to include Ns.
createMutabilityMatrix

Builds a mutability model
minNumMutationsTune

Parameter tuning for minNumMutations
makeAverage1merMut

Make a 1-mer mutability model by averaging over a 5-mer mutability model
makeAverage1merSub

Make a 1-mer substitution model by averaging over a 5-mer substitution model
MutationDefinition-class

S4 class defining replacement and silent mutation definitions
extendSubstitutionMatrix

Extends a substitution model to include Ns.
observedMutations

Calculate observed numbers of mutations
DensityThreshold-class

Output of the dens method of findThreshold
createRegionDefinition

Creates a RegionDefinition
createMutationDefinition

Creates a MutationDefinition
TargetingModel-class

S4 class defining a targeting model
summarizeBaseline

Calculate BASELINe summary statistics
RegionDefinition-class

S4 class defining a region definition
testBaseline

Two-sided test of BASELINe PDFs
plotBaselineDensity

Plots BASELINe probability density functions
editBaseline

Edit the Baseline object
expectedMutations

Calculate expected mutation frequencies
shmulateSeq

Simulate mutations in a single sequence
makeDegenerate5merSub

Make a degenerate 5-mer substitution model based on a 1-mer substitution model
makeDegenerate5merMut

Make a degenerate 5-mer mutability model based on a 1-mer mutability model
minNumSeqMutationsTune

Parameter tuning for minNumSeqMutations
plotGmmThreshold

Plot findThreshold results for the gmm method
shmulateTree

Simulate mutations in a lineage tree
slideWindowDb

Sliding window approach towards filtering sequences in a data.frame
clearConsole

Clears the console
slideWindowSeq

Sliding window approach towards filtering a single sequence
slideWindowTune

Parameter tuning for sliding window approach
writeTargetingDistance

Write targeting model distances to a file
collapseClones

Constructs effective clonal sequences for all clones
plotMutability

Plot mutability probabilities
getPlatform

Determines the OS platform being used
findThreshold

Find distance threshold
plotBaselineSummary

Plots BASELINe summary statistics
slideWindowTunePlot

Visualize parameter tuning for sliding window approach
plotDensityThreshold

Plot findThreshold results for the density method
shazam

The shazam package
plotTune

Visualize parameter tuning for minNumMutations and minNumSeqMutations
HH_S5F

Human heavy chain, silent, 5-mer, functional targeting model.
HKL_S1F

Human kappa and lambda chain, silent, 1-mer, functional substitution model.
MK_RS5NF

Mouse kappa light chain, replacement and silent, 5-mer, non-functional targeting model.