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NEW!!! rpkg.net flagship R package "quickcode" now available in CRAN quickcode TM
ClusTCR2
View on CRAN: Click
here
Download and install ClusTCR2 package within the R console
Install from CRAN:
install.packages("ClusTCR2")
Install from Github:
library("remotes")
install_github("cran/ClusTCR2")
Install by package version:
library("remotes")
install_version("ClusTCR2", "1.7.3.01")
Attach the package and use:
library("ClusTCR2")
Maintained by
Kerry A. Mullan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2024-05-16
Latest Update: 2024-05-16
Description:
Enhancing T cell receptor (TCR) sequence analysis, 'ClusTCR2', based on 'ClusTCR' python program, leverages Hamming distance to compare the complement-determining region three (CDR3) sequences for sequence similarity, variable gene (V gene) and length. The second step employs the Markov Cluster Algorithm to identify clusters within an undirected graph, providing a summary of amino acid motifs and matrix for generating network plots. Tailored for single-cell RNA-seq data with integrated TCR-seq information, 'ClusTCR2' is integrated into the Single Cell TCR and Expression Grouped Ontologies (STEGO) R application or 'STEGO.R'. See the two publications for more details. Sebastiaan Valkiers, Max Van Houcke, Kris Laukens, Pieter Meysman (2021) <doi:10.1093/bioinformatics/btab446>, Kerry A. Mullan, My Ha, Sebastiaan Valkiers, Nicky de Vrij, Benson Ogunjimi, Kris Laukens, Pieter Meysman (2023) <doi:10.1101/2023.09.27.559702>.
How to cite:
Kerry A. Mullan (2024). ClusTCR2: Identifying Similar T Cell Receptor Hyper-Variable Sequences with 'ClusTCR2'. R package version 1.7.3.01, https://cran.r-project.org/web/packages/ClusTCR2
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