shazam1.2.0 package

Immunoglobulin Somatic Hypermutation Analysis

Baseline-class

S4 class defining a BASELINe (selection) object

calcBaseline

Calculate the BASELINe PDFs (including for regions that include CDR3 a...

calcExpectedMutations

Calculate expected mutation frequencies of a sequence

calcObservedMutations

Count the number of observed mutations in a sequence.

calcTargetingDistance

Calculates a 5-mer distance matrix from a TargetingModel object

calculateMutability

Calculate total mutability

collapseClones

Constructs effective clonal sequences for all clones

consensusSequence

Construct a consensus sequence

convertNumbering

convertNumbering: IMGT-Kabat number conversion

createBaseline

Creates a Baseline object

createMutabilityMatrix

Builds a mutability model

createMutationDefinition

Creates a MutationDefinition

createRegionDefinition

Creates a RegionDefinition

createSubstitutionMatrix

Builds a substitution model

createTargetingMatrix

Calculates a targeting rate matrix

createTargetingModel

Creates a TargetingModel

DensityThreshold-class

Output of the dens method of findThreshold

distToNearest

Distance to nearest neighbor

editBaseline

Edit the Baseline object

expectedMutations

Calculate expected mutation frequencies

extendMutabilityMatrix

Extends a mutability model to include Ns.

extendSubstitutionMatrix

Extends a substitution model to include Ns.

findThreshold

Find distance threshold

GmmThreshold-class

Output of the gmm method of findThreshold

groupBaseline

Group BASELINe PDFs

IMGT_SCHEMES

IMGT unique numbering schemes

makeAverage1merMut

Make a 1-mer mutability model by averaging over a 5-mer mutability mod...

makeAverage1merSub

Make a 1-mer substitution model by averaging over a 5-mer substitution...

makeDegenerate5merMut

Make a degenerate 5-mer mutability model based on a 1-mer mutability m...

makeDegenerate5merSub

Make a degenerate 5-mer substitution model based on a 1-mer substituti...

makeGraphDf

Build a data.frame from a ChangeoClone and an igraph object containing...

minNumMutationsTune

Parameter tuning for minNumMutations

minNumSeqMutationsTune

Parameter tuning for minNumSeqMutations

MutabilityModel-class

S4 class defining a mutability model

MUTATION_SCHEMES

Amino acid mutation definitions

MutationDefinition-class

S4 class defining replacement and silent mutation definitions

observedMutations

Calculate observed numbers of mutations

plotBaselineDensity

Plots BASELINe probability density functions

plotBaselineSummary

Plots BASELINe summary statistics

plotDensityThreshold

Plot findThreshold results for the density method

plotGmmThreshold

Plot findThreshold results for the gmm method

plotMutability

Plot mutability probabilities

plotSlideWindowTune

Visualize parameter tuning for sliding window approach

plotTune

Visualize parameter tuning for minNumMutations and minNumSeqMutations

RegionDefinition-class

S4 class defining a region definition

setRegionBoundaries

Build a RegionDefinition object that includes CDR3 and FWR4.

shazam-package

shazam: Immunoglobulin Somatic Hypermutation Analysis

shazam

The shazam package

shmulateSeq

Simulate mutations in a single sequence

shmulateTree

Simulate mutations in a lineage tree

slideWindowDb

Sliding window approach towards filtering sequences in a data.frame

slideWindowSeq

Sliding window approach towards filtering a single sequence

slideWindowTune

Parameter tuning for sliding window approach

slideWindowTunePlot

slideWindowTunePlot - plotSlideWindowTune backward compatability

summarizeBaseline

Calculate BASELINe summary statistics

TargetingMatrix-class

S4 class defining a targeting matrix

TargetingModel-class

S4 class defining a targeting model

testBaseline

Two-sided test of BASELINe PDFs

writeTargetingDistance

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>.

  • Maintainer: Susanna Marquez
  • License: AGPL-3
  • Last published: 2023-10-02