Package: shazam 1.3.2.999

Susanna Marquez

shazam: Immunoglobulin Somatic Hypermutation Analysis

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>.

Authors:Mohamed Uduman [aut], Namita Gupta [aut], Susanna Marquez [aut, cre], Julian Zhou [aut], Nima Nouri [aut], Noah Yann Lee [aut], Ang Cui [ctb], Jason Vander Heiden [aut], Gur Yaari [aut], Steven Kleinstein [aut, cph]

shazam_1.3.2.999.tar.gz
shazam_1.3.2.999.zip(r-4.7)shazam_1.3.2.999.zip(r-4.6)shazam_1.3.2.999.zip(r-4.5)
shazam_1.3.2.999.tgz(r-4.6-any)shazam_1.3.2.999.tgz(r-4.5-any)
shazam_1.3.2.999.tar.gz(r-4.7-any)shazam_1.3.2.999.tar.gz(r-4.6-any)
shazam_1.3.2.999.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
shazam/json (API)

# Install 'shazam' in R:
install.packages('shazam', repos = c('https://immcantation.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/immcantation/shazam/issues

On CRAN:

Conda:

9.26 score 2 stars 2 packages 495 scripts 1.2k downloads 51 exports 91 dependencies

Last updated from:cdf9f1c671. Checks:7 WARNING, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64WARNING311
source / vignettesOK331
linux-release-x86_64WARNING328
macos-release-arm64WARNING175
macos-oldrel-arm64WARNING147
windows-develWARNING248
windows-releaseWARNING231
windows-oldrelWARNING244
wasm-releaseOK178

Exports:as.data.framecalcBaselinecalcExpectedMutationscalcObservedMutationscalcTargetingDistancecalculateMutabilitycollapseClonesconsensusSequenceconvertNumberingcreateBaselinecreateMutabilityMatrixcreateMutationDefinitioncreateRegionDefinitioncreateSubstitutionMatrixcreateTargetingMatrixcreateTargetingModeldistToNearesteditBaselineexpectedMutationsextendMutabilityMatrixextendSubstitutionMatrixfindThresholdgroupBaselinemakeAverage1merMutmakeAverage1merSubmakeDegenerate5merMutmakeDegenerate5merSubmakeGraphDfminNumMutationsTuneminNumSeqMutationsTuneobservedMutationsplotplotBaselineDensityplotBaselineSummaryplotDensityThresholdplotGmmThresholdplotMutabilityplotSlideWindowTuneplotTuneprintsetRegionBoundariesshmulateSeqshmulateTreeslideWindowDbslideWindowSeqslideWindowTuneslideWindowTunePlotsummarizeBaselinesummarytestBaselinewriteTargetingDistance

Dependencies:abindade4airralakazamapeBHBiobaseBiocGenericsBiocParallelBiostringsbitbit64bitopscigarilloclicliprcodetoolscpp11crayonDelayedArraydigestdiptestdoParalleldplyrfarverforeachformatRfutile.loggerfutile.optionsgenericsGenomicAlignmentsGenomicRangesggplot2gluegtablehmsigraphIRangesisobanditeratorsjsonliteKernSmoothlabelinglambda.rlatticelazyevallifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsnlmepillarpixmappkgconfigprettyunitsprogresspurrrR6RColorBrewerRcppRcppArmadilloreadrRhtslibrlangRsamtoolsS4ArraysS4VectorsS7scalessegmentedSeqinfoseqinrsnowspSparseArraystringistringrSummarizedExperimenttibbletidyrtidyselecttzdbutf8vctrsviridisLitevroomwithrXVectoryaml

Shazam: Simulating sequence mutations
Simulate mutations in a single sequence | Simulate mutations in a lineage tree
Rendered fromShmulate-Vignette.Rmdusingknitr::rmarkdown

Last update: 2026-04-30
Started: 2018-03-16

Shazam: Tuning clonal assignment thresholds with nearest neighbor distances
Example data | Calculating nearest neighbor distances (heavy chain sequences) | Calculating nearest neighbor distances (single-cell paired heavy and light chain sequences) | Using nearest neighbor distances to determine clonal assignment thresholds | Threshold determination by manual inspection | Automated threshold detection via smoothed density | Automated threshold detection via a mixture model | Calculating nearest neighbor distances independently for subsets of data | Calculating nearest neighbor distances across groups rather than within a groups | Speeding up pairwise-distance-matrix calculations with subsampling
Rendered fromDistToNearest-Vignette.Rmdusingknitr::rmarkdown

Last update: 2024-04-02
Started: 2015-02-04

Shazam: Quantification of selection pressure
Example data | Preprocessing | Constructing clonal consensus sequences | Incorporating lineage information | Calculate selection PDFs for individual sequences | Calculating selection in multiple steps | Calculating selection in one step | Using alternative mutation definitions and models | Group and convolve individual selection distributions | Grouping by a single annotation | Subsetting and grouping by multiple annotations | Convolving variables at multiple levels | Testing the difference in selection PDFs between groups | Plot and compare selection scores for groups | Editing a field in a Baseline object
Rendered fromBaseline-Vignette.Rmdusingknitr::rmarkdown

Last update: 2024-04-02
Started: 2015-04-28

Shazam: Inferring SHM targeting models
Example data | Infer targeting model (substitution and mutability) | Visualize targeting model | Calculate targeting distance matrix
Rendered fromTargeting-Vignette.Rmdusingknitr::rmarkdown

Last update: 2024-04-02
Started: 2015-04-25

Shazam: Mutation analysis
Example data | Calculate the counts and frequencies of mutations over the entire sequence | Calculate mutations within subregions | Use amino acid physicochemical properties to define mutations
Rendered fromMutation-Vignette.Rmdusingknitr::rmarkdown

Last update: 2023-11-06
Started: 2017-04-03