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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. 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.

The mission of immunarch is to make immune repertoire data analysis as easy and possible - even with R. Please feel free to check it here: https://immunarch.com/

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

See tcR website for more information, manual and examples: http://imminfo.github.io/tcr/

If you have any questions, suggestions or bug reports, feel free to raise an issue here: https://github.com/imminfo/tcr/issues

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

Warning! tcR internally expects columns with nucleotide and amino acid CDR3 sequences and columns with gene segments to have character class, not factor class. Use stringsAsFactors=FALSE parameter if you use R functions for parsing files with tables (.csv, .xls and others).

Note for installation on Macs with OSX Yosemite (and potentially other versions): if you receive a compilation error, modify tcR/src/Makvars to:

CXX=clang++

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Version

Install

install.packages('tcR')

Monthly Downloads

141

Version

2.2.4

License

Apache License 2.0

Maintainer

Last Published

March 25th, 2019

Functions in tcR (2.2.4)

check.distribution

Check for adequaty of distrubution.

clonal.space.homeostasis

Clonal space homeostasis.

Columns statistics.

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

Tables with genetic code.

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.

Generate k-mers.

contamination.stats

Contamination filtering.

Generate random nucleotide TCR sequences.

Check if a given object has a given class.

group.clonotypes

Get all unique clonotypes.

intersectClonesets

Intersection between sets of sequences or any elements.

convergence.index

Compute convergence characteristics of repertoires.

Overlap Z-score.

Parse input table files with the immune receptor repertoire data.

General function for the repertoire overlap evaluation.

Shared repertoire analysis.

Normalised log assymetry.

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

find.clonotypes

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

Shuffling data frames.

MiTCR data frame basic statistics.

Diversity evaluation using rarefaction.

Functions for working with aminoacid sequences.

Compute the Euclidean distance among principal components.

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

Choose the right column.

barcodes.to.reads

Rearrange columns with counts for clonesets.

Get a sample from matrix with probabilities.

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

Fix names in lists.

Reverse given character vector by the given n-plets.

List with assembling probabilities of beta chain TCRs.

Start MiTCR directly from the package.

Bootstrap for data frames in package tcR.

find.similar.sequences

Find similar sequences.

GC-content of a nucleotide sequences.

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

Print the given message if second parameter is a TRUE.

Information measures.

vis.clonal.dynamics

Visualise clonal dynamics among time points.

vis.clonal.space

Visualise occupied by clones homeostatic space among Samples or groups.

Get a random subset from a data.frame.

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

get.all.substrings

Get all substrings for the given sequence.

Log-likelihood.

tailbound.proportion

Proportions of specifyed subsets of clones.

segments.alphabets

Alphabets of TCR and Ig gene segments.

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

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

Radar-like / spider-like plots.

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

get.deletions.alpha

Compute the number of deletions in MiTCR data frames.

Twins alpha-beta chain data

mutated.neighbours

Get vertex neighbours.

inverse.simpson

Distribution evaluation.

Profile of sequences of equal length.

vis.kmer.histogram

Plot of the most frequent kmers.

matrixSubgroups

Get all values from the matrix corresponding to specific groups.

Logo - plots for amino acid and nucletide profiles.

vis.top.proportions

Visualisation of top clones proportions.

vis.shared.clonotypes

Visualisation of shared clonotypes occurrences among repertoires.

Simple functions for manipulating progress bars.

set.people.vector

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

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

Get kmers from sequences.

Parse input table files with immune receptor repertoire data.

General function for the repertoire diversity estimation.

Perform PCA on segments frequency data.

Parse input files or folders with immune receptor repertoire data.

Set new columns "Rank" and "Index".

vis.rarefaction

Rarefaction statistics visualisation.

mutation.network

Make mutation network for the given repertoire.

shared.repertoire

Shared TCR repertoire managing and analysis

DNA reverse complementing and translation.

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

vis.group.boxplot

Boxplot for groups of observations.

set.group.vector

Set group attribute for vertices of a mutation network

PCA result visualisation

vis.number.count

Plot a histogram of counts.

Plot a histogram of lengths.

Histogram of segments usage.