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tcR

The tcR package is no longer supported and current issues will not be fixed.

A new package is available that is designed to replace tcR called immunarch: https://immunarch.com/

We have solved most of the problems tcR package had and improved the overall pipeline, providing functions for painless repertoire file parsing and publication-ready plot making. We will be happy to help you to integrate the new package into your pipelines. Please do not hesitate to contact us via emails on https://immunarch.com/ or via issues on https://github.com/immunomind/immunarch, should any question arise.

Sincerely, immunarch dev team and Vadim I. Nazarov, lead developer

tcR is a platform designed for TCR and Ig repertoire data analysis in R after preprocessing data with software tools for CDR3 extraction and gene segments aligning (MiTCR, MiXCR, MiGEC, ImmunoSEQ, IMSEQ, etc.). With the power and flexibility of R language and procedures supported by tcR users can perform advanced statistical analysis of TCR and Ig repertoires. The package was published in BMC Bioinformatics, please cite if you use it:

Nazarov et al., tcR: an R package for T cell receptor repertoire advanced data analysis

The project was developed mainly in the Laboratory of Comparative and Functional Genomics.

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Version

Install

install.packages('tcR')

Monthly Downloads

155

Version

2.3.2

License

Apache License 2.0

Homepage

https://immunarch.com/

Maintainer

Last Published

June 9th, 2020

Functions in tcR (2.3.2)

List with assembling probabilities of beta chain TCRs.

Apply function to every pair of data frames from a list.

MiTCR data frame basic statistics.

barcodes.to.reads

Rearrange columns with counts for clonesets.

Tables with genetic code.

Bootstrap for data frames in package tcR.

Normalised log assymetry.

check.distribution

Check for adequaty of distrubution.

Functions for working with aminoacid sequences.

cosine.similarity

Set and vector similarity measures.

Internal function. Add legend to a grid of plots and remove legend from all plots of a grid.

Choose the right column.

Fix names in lists.

Repertoires' analysis using information measures applied to V- and J- segment frequencies.

find.similar.sequences

Find similar sequences.

convergence.index

Compute convergence characteristics of repertoires.

Generate random nucleotide TCR sequences.

Generate k-mers.

Information measures.

Print the given message if second parameter is a TRUE.

clonal.space.homeostasis

Clonal space homeostasis.

contamination.stats

Contamination filtering.

matrixSubgroups

Get all values from the matrix corresponding to specific groups.

Columns statistics.

Shared repertoire analysis.

get.all.substrings

Get all substrings for the given sequence.

In-frame / out-of-frame sequences filter.

find.clonotypes

Find target clonotypes and get columns' value corresponded to that clonotypes.

Fix alleles / genes by removing allele information / unnecessary colons.

Profile of sequences of equal length.

inverse.simpson

Distribution evaluation.

GC-content of a nucleotide sequences.

Copy the up-triangle matrix values to low-triangle.

Reverse given character vector by the given n-plets.

Get kmers from sequences.

intersectClonesets

Intersection between sets of sequences or any elements.

get.deletions.alpha

Compute the number of deletions in MiTCR data frames.

Check if a given object has a given class.

Monte Carlo permutation test for pairwise and one-vs-all-wise within- and inter-group differences in a set of repertoires.

Compute the Euclidean distance among principal components.

Get a random subset from a data.frame.

Save tcR data frames to disk as text files or gzipped text files.

General function for the repertoire overlap evaluation.

Make and manage the table of the most frequent k-mers.

Log-likelihood.

Parse input table files with immune receptor repertoire data.

set.people.vector

Set and get attributes of a mutation network related to source people.

Simple functions for manipulating progress bars.

Diversity evaluation using rarefaction.

Get a sample from matrix with probabilities.

Shuffling data frames.

Perform PCA on segments frequency data.

Overlap Z-score.

vis.group.boxplot

Boxplot for groups of observations.

group.clonotypes

Get all unique clonotypes.

mutation.network

Make mutation network for the given repertoire.

Resample data frame using values from the column with number of clonesets.

mutated.neighbours

Get vertex neighbours.

vis.shared.clonotypes

Visualisation of shared clonotypes occurrences among repertoires.

segments.alphabets

Alphabets of TCR and Ig gene segments.

vis.top.proportions

Visualisation of top clones proportions.

Parse input table files with the immune receptor repertoire data.

vis.kmer.histogram

Plot of the most frequent kmers.

Plot a histogram of lengths.

shared.repertoire

Shared TCR repertoire managing and analysis

Twins alpha-beta chain data

Radar-like / spider-like plots.

General function for the repertoire diversity estimation.

Set new columns "Rank" and "Index".

Parse input files or folders with immune receptor repertoire data.

Get samples from a repertoire slice-by-slice or top-by-top and apply function to them.

DNA reverse complementing and translation.

Start MiTCR directly from the package.

Histogram of segments usage.

Logo - plots for amino acid and nucletide profiles.

vis.rarefaction

Rarefaction statistics visualisation.

vis.clonal.space

Visualise occupied by clones homeostatic space among Samples or groups.

vis.clonal.dynamics

Visualise clonal dynamics among time points.

Perform sequential cross starting from the top of a data frame.

tailbound.proportion

Proportions of specifyed subsets of clones.

set.group.vector

Set group attribute for vertices of a mutation network

vis.number.count

Plot a histogram of counts.

PCA result visualisation