Spectral Clustering-Based Method for Identifying B Cell Clones

Provides a computational framework for B cell clones identification from adaptive immune receptor repertoire sequencing (AIRR-Seq) datasets. Three models are included (identical, hierarchical, and spectral) that perform clustering among sequences of BCRs/IGs (B cell receptors/immunoglobulins) which share the same V gene, J gene and junction length. Nouri N and Kleinstein SH (2018) . Gupta NT, et al. (2017) .


SCOPer (Spectral Clustering for clOne Partitioning) provides a computational framework for unsupervised identification B cell clones from adaptive immune receptor repertoire sequencing (AIRR-Seq) datasets. This method performs spectral clustering of the B cell receptor (BCR) junction region within groups of BCR sequences sharing the same V gene, J gene, and junction length. Rather than a fixed threshold, SCOPe uses an adaptive threshold for clustering sequences to determine the local sequence neighborhood, which offers an improvement in both the sensitivity and specificity over a simple fixed threshold for all junction lengths. SCOPer is part of the Immcantation analysis framework.


For help and questions please contact the Immcantation Group


Version 0.1.0: October 4, 2018

Initial public release.

Reference manual

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0.2.0 by Nima Nouri, 8 months ago


Report a bug at https://bitbucket.org/kleinstein/scoper/issues

Browse source code at https://github.com/cran/scoper

Authors: Nima Nouri [aut, cre] , Jason Vander Heiden [ctb] , Steven Kleinstein [aut, cph]

Documentation:   PDF Manual  

CC BY-SA 4.0 license

Imports alakazam, shazam, doParallel, foreach, dplyr, Rcpp, seqinr, data.table, stringi, stringr, methods, stats, rlang

Depends on ggplot2

Suggests knitr, rmarkdown, testthat

Linking to Rcpp

System requirements: C++11

See at CRAN