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>.

Version: 0.1.10
Depends: R (≥ 3.1.2), ggplot2 (≥ 2.0.0), stringi (≥ 1.1.3)
Imports: alakazam (≥ 0.2.11), ape, diptest, doParallel, dplyr (≥ 0.5.0), foreach, graphics, grid, igraph, iterators, kedd, KernSmooth, lazyeval, MASS, methods, parallel, progress, SDMTools, scales, seqinr, stats, tidyr, utils
Suggests: knitr, rmarkdown, testthat
Published: 2018-09-20
Author: Mohamed Uduman [aut], Gur Yaari [aut], Namita Gupta [aut], Jason Vander Heiden [aut, cre], Ang Cui [ctb], Susanna Marquez [ctb], Julian Zhou [ctb], Nima Nouri [ctb], Steven Kleinstein [aut, cph]
Maintainer: Jason Vander Heiden <jason.vanderheiden at yale.edu>
BugReports: https://bitbucket.org/kleinstein/shazam/issues
License: CC BY-SA 4.0
URL: http://shazam.readthedocs.io
NeedsCompilation: no
Citation: shazam citation info
Materials: README NEWS
CRAN checks: shazam results

Downloads:

Reference manual: shazam.pdf
Vignettes: Selection quantification
Distance to nearest neighbor
Mutation analysis
Simulating sequence mutations
SHM targeting models
Package source: shazam_0.1.10.tar.gz
Windows binaries: r-devel: shazam_0.1.10.zip, r-release: shazam_0.1.10.zip, r-oldrel: shazam_0.1.9.zip
OS X binaries: r-release: shazam_0.1.9.tgz, r-oldrel: shazam_0.1.9.tgz
Old sources: shazam archive

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