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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) tools:::Rd_expr_doi("10.1093/bioinformatics/btv359"), Yaari, et al (2012) tools:::Rd_expr_doi("10.1093/nar/gks457"), Yaari, et al (2013) tools:::Rd_expr_doi("10.3389/fimmu.2013.00358"), Cui, et al (2016) tools:::Rd_expr_doi("10.4049/jimmunol.1502263").
Maintainer: Susanna Marquez susanna.marquez@yale.edu
Authors:
Mohamed Uduman mohamed.uduman@yale.edu
Namita Gupta namita.gupta@yale.edu
Julian Zhou julian.zhou@yale.edu
Nima Nouri nima.nouri@yale.edu
Noah Yann Lee noah.yann.lee@yale.edu
Jason Vander Heiden jason.vanderheiden@gmail.com
Gur Yaari gur.yaari@biu.ac.il
Steven Kleinstein steven.kleinstein@yale.edu [copyright holder]
Other contributors:
Ang Cui angcui@mit.edu [contributor]
Useful links: