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tcR (version 2.0)
Advanced Data Analysis of T Cell Receptor Repertoires
Description
Platform for the advanced analysis of T cell receptor repertoires data and visualisation of the analysis results.
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Install
install.packages('tcR')
Monthly Downloads
140
Version
2.0
License
Apache License 2.0
Maintainer
Vadim Nazarov
Last Published
May 14th, 2015
Functions in tcR (2.0)
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AA_TABLE
Tables with genetic code.
codon.variants
Functions for working with aminoacid sequences.
sample2D
Get a sample from matrix with probabilities.
geneUsage
Gene usage.
matrixdiagcopy
Copy the up-triangle matrix values to low-triangle.
column.summary
Columns statistics.
group.clonotypes
Get all unique clonotypes.
vis.kmer.histogram
Plot of the most frequent kmers.
rarefaction
Diversity evaluation using rarefaction.
repOverlap
General function for the repertoire overlap evaluation.
pca.segments
Perform PCA on segments frequency data.
vis.number.count
Plot a histogram of counts.
parse.folder
Parse input table files with immune receptor repertoire data.
spectratyping
Spectratype plot.
barcodes.to.reads
Rearrange columns with counts for clonesets.
get.inframes
In-frame / out-of-frame sequences filter.
bootstrap.tcr
Bootstrap for data frames in package tcR.
generate.kmers
Generate k-mers.
vis.heatmap
Heatmap.
segments.alphabets
Alphabets of TCR and Ig gene segments.
startmitcr
Start MiTCR directly from the package.
permutedf
Shuffling data frames.
set.pb
Simple functions for manipulating progress bars.
get.deletions.alpha
Compute the number of deletions in MiTCR data frames.
segments.list
Segment data.
vis.count.len
Plot a histogram of lengths.
clonal.space.homeostasis
Clonal space homeostasis.
set.group.vector
Set group attribute for vertices of a mutation network
apply.symm
Apply function to every pair of data frames from a list.
find.clonotypes
Find target clonotypes and get columns' value corresponded to that clonotypes.
kmer.table
Make and manage the table of the most frequent k-mers.
beta.prob
List with assembling probabilities of beta chain TCRs.
check.distribution
Check for adequaty of distrubution.
get.n.barcodes
Resample data frame using values from the column with number of clonesets.
parse.cloneset
Parse input table files with the immune receptor repertoire data.
repDiversity
General function for the repertoire diversity estimation.
vis.top.proportions
Visualisation of top clones proportions.
revcomp
DNA reverse complementing and translation.
cosine.similarity
Set and vector similarity measures.
set.people.vector
Set and get attributes of a mutation network related to source people.
set.rank
Set new columns "Rank" and "Index".
cosine.sharing
Shared repertoire analysis.
contamination.stats
Contamination filtering.
get.kmers
Get kmers from sequences.
vis.clonal.dynamics
Visualise clonal dynamics among time points.
top.cross
Perform sequential cross starting from the top of a data frame.
vis.gene.usage
Histogram of segments usage.
vis.pca
PCA result visualisation
assymetry
Normalised log assymetry.
find.similar.sequences
Find similar sequences.
generate.tcr
Generate random nucleotide TCR sequences.
entropy
Information measures.
shared.repertoire
Shared TCR repertoire managing and analysis
inverse.simpson
Distribution evaluation.
vis.rarefaction
Rarefaction statistics visualisation.
vis.radarlike
Radar-like / spider-like plots.
gibbs.sampler
Gibbs Sampler.
loglikelihood
Log-likelihood.
mutation.network
Make mutation network for the given repertoire.
mutated.neighbours
Get vertex neighbours.
reverse.string
Reverse given character vector by the given n-plets.
cloneset.stats
MiTCR data frame basic statistics.
top.fun
Get samples from a repertoire slice-by-slice or top-by-top and apply function to them.
intersectClonesets
Intersection between sets of sequences or any elements.
get.all.substrings
Get all substrings for the given sequence.
tailbound.proportion
Proportions of specifyed subsets of clones.
twinsdata
Twins alpha-beta chain data
vis.clonal.space
Visualise occupied by clones homeostatic space among Samples or groups.
vis.logo
Logo - plots for amino acid and nucletide profiles.
gc.content
GC-content of a nucleotide sequences.
sample.clones
Get a random subset from a data.frame.
vis.group.boxplot
Boxplot for groups of observations.
entropy.seg
Repertoires' analysis using information measures applied to V- and J- segment frequencies.
has.class
Check if a given object has a given class.
kmer.profile
Profile of sequences of equal length.
convergence.index
Compute convergence characteristics of repertoires.