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tcR

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

39

Version

2.2.1.11

License

Apache License 2.0

Maintainer

Vadim Nazarov

Last Published

April 22nd, 2016

Functions in tcR (2.2.1.11)

rarefaction

Diversity evaluation using rarefaction.
ozScore

Overlap Z-score.
vis.logo

Logo - plots for amino acid and nucletide profiles.
has.class

Check if a given object has a given class.
gibbs.sampler

Gibbs Sampler.
pca2euclid

Compute the Euclidean distance among principal components.
sample.clones

Get a random subset from a data.frame.
cloneset.stats

MiTCR data frame basic statistics.
vis.clonal.space

Visualise occupied by clones homeostatic space among Samples or groups.
kmer.table

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

Compute convergence characteristics of repertoires.
pca.segments

Perform PCA on segments frequency data.
repLoad

Parse input files or folders with immune receptor repertoire data.
AA_TABLE

Tables with genetic code.
entropy.seg

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

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

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

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

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

Contamination filtering.
set.people.vector

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

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

PCA result visualisation
tailbound.proportion

Proportions of specifyed subsets of clones.
top.fun

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

Gene usage.
find.similar.sequences

Find similar sequences.
get.deletions.alpha

Compute the number of deletions in MiTCR data frames.
codon.variants

Functions for working with aminoacid sequences.
vis.count.len

Plot a histogram of lengths.
entropy

Information measures.
check.distribution

Check for adequaty of distrubution.
segments.list

Segment data.
get.all.substrings

Get all substrings for the given sequence.
loglikelihood

Log-likelihood.
kmer.profile

Profile of sequences of equal length.
vis.kmer.histogram

Plot of the most frequent kmers.
shared.repertoire

Shared TCR repertoire managing and analysis
inverse.simpson

Distribution evaluation.
set.rank

Set new columns "Rank" and "Index".
vis.group.boxplot

Boxplot for groups of observations.
vis.shared.clonotypes

Visualisation of shared clonotypes occurrences among repertoires.
matrixSubgroups

Get all values from the matrix corresponding to specific groups.
generate.kmers

Generate k-mers.
startmitcr

Start MiTCR directly from the package.
group.clonotypes

Get all unique clonotypes.
apply.symm

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

Parse input table files with immune receptor repertoire data.
set.pb

Simple functions for manipulating progress bars.
mutated.neighbours

Get vertex neighbours.
column.summary

Columns statistics.
sample2D

Get a sample from matrix with probabilities.
clonal.space.homeostasis

Clonal space homeostasis.
gc.content

GC-content of a nucleotide sequences.
fix.alleles

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

Shared repertoire analysis.
generate.tcr

Generate random nucleotide TCR sequences.
intersectClonesets

Intersection between sets of sequences or any elements.
beta.prob

List with assembling probabilities of beta chain TCRs.
barcodes.to.reads

Rearrange columns with counts for clonesets.
repDiversity

General function for the repertoire diversity estimation.
spectratyping

Spectratype plot.
segments.alphabets

Alphabets of TCR and Ig gene segments.
twinsdata

Twins alpha-beta chain data
repOverlap

General function for the repertoire overlap evaluation.
cosine.similarity

Set and vector similarity measures.
vis.clonal.dynamics

Visualise clonal dynamics among time points.
matrixdiagcopy

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

Radar-like / spider-like plots.
vis.heatmap

Heatmap.
parse.cloneset

Parse input table files with the immune receptor repertoire data.
vis.gene.usage

Histogram of segments usage.
assymetry

Normalised log assymetry.
vis.rarefaction

Rarefaction statistics visualisation.
permutedf

Shuffling data frames.
mutation.network

Make mutation network for the given repertoire.
vis.number.count

Plot a histogram of counts.
reverse.string

Reverse given character vector by the given n-plets.
get.kmers

Get kmers from sequences.
bootstrap.tcr

Bootstrap for data frames in package tcR.
set.group.vector

Set group attribute for vertices of a mutation network
find.clonotypes

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

DNA reverse complementing and translation.
vis.top.proportions

Visualisation of top clones proportions.
get.n.barcodes

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