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>.

Package overview README.md Distance to nearest neighbor Mutation analysis Selection quantification SHM targeting models Simulating sequence mutations Shazam: Inferring SHM targeting models Shazam: Mutation analysis Shazam: Quantification of selection pressure Shazam: Simulating sequence mutations Shazam: Tuning clonal assignment thresholds with nearest neighbor distances

Vignettes Man pages API and functions Files

Package details
Author	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]
Maintainer	Susanna Marquez <susanna.marquez@yale.edu>
License	AGPL-3
Version	1.2.0
URL	http://shazam.readthedocs.io
Package repository	View on CRAN
Installation	Install the latest version of this package by entering the following in R: `install.packages("shazam")`