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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>.

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conda 2.2 MB | noarch/r-shazam-1.1.2-r42h3121a25_1.tar.bz2  2 years and 3 months ago 2128 main
conda 2.2 MB | noarch/r-shazam-1.1.2-r41h3121a25_0.tar.bz2  2 years and 4 months ago 249 main

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