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tcR (version 1.0)
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
1.0
License
Apache License 2.0
Maintainer
Vadim Nazarov
Last Published
December 12th, 2014
Functions in tcR (1.0)
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get.kmers
Get kmers from sequences.
apply.symm
Apply function to every pair of data frames from a list.
check.distribution
Check for adequaty of distrubution.
codon.variants
Functions for working with aminoacid sequences.
set.pb
Simple functions for manipulating progress bars.
get.n.barcodes
Resample data frame using values from the column with number of clonesets.
cosine.sharing
Shared repertoire analysis.
convergence.index
Compute convergence characteristics of repertoires.
kmer.profile
Profile of sequences of equal length.
sample.clones
Get a random subset from a data.frame.
permutedf
Shuffling data frames.
contamination.stats
Contamination filtering.
has.class
Check if a given object has a given class.
set.rank
Set new columns "Rank" and "Index".
sample2D
Get a sample from matrix with probabilities.
generate.kmers
Generate k-mers.
AA_TABLE
Tables with genetic code.
top.cross
Perform sequential cross starting from the top of a data.frame.
barcodes.to.reads
Rearrange columns with counts for clonesets.
matrixdiagcopy
Copy the up-triangle matrix values to low-triangle.
parse.file
Parse input file with the given filename to a data frame.
find.clonotypes
Find target clonotypes and get columns' value corresponded to that clonotypes.
twinsdata
Twins alpha-beta chain data
pca.segments
Perform PCA on segments frequency data.
generate.tcr
Generate random nucleotide TCR sequences.
beta.prob
List with assembling probabilities of beta chain TCRs.
top.fun
Get samples from a repertoire slice-by-slice or top-by-top and apply function to them.
loglikelihood
Log-likelihood.
tailbound.proportion
Proportions of specifyed subsets of clones.
vis.radarlike
Radar-like / spider-like plots.
vis.rarefaction
Rarefaction statistics visualisation.
vis.group.boxplot
Boxplot for groups of observations.
vis.clonal.dynamics
Visualise clonal dynamics among time points.
vis.count.len
Plot a histogram of lengths.
revcomp
DNA reverse complementing and translation.
vis.heatmap
Heatmap.
vis.top.proportions
Visualisation of top clones proportions.
reverse.string
Reverse given character vector by the given n-plets.
parse.file.list
Parse files from the given vector or list with filepaths and return list with data.frames.
vis.pca
PCA result visualisation
spectratyping
Spectratype plot.
gc.content
GC-content of a nucleotide sequences.
vis.kmer.histogram
Plot of the most frequent kmers.
cosine.similarity
Set and vector similarity measures.
segments.list
Segment data.
kmer.table
Make and manage the table of the most frequent k-mers.
freq.segments
V- and J-segments frequency.
assymetry
Normalised log assymetry.
gibbs.sampler
Gibbs Sampler.
bootstrap.tcr
Bootstrap for data frames in package tcR.
get.inframes
In-frame / out-of-frame sequences filter.
entropy.seg
Repertoires' analysis using information measures applied to V- and J- segment frequencies.
entropy
Information measures.
get.deletions.alpha
Compute the number of deletions in MiTCR data frames.
rarefaction
Diversity evaluation using rarefaction.
inverse.simpson
Distribution evaluation.
shared.repertoire
Shared TCR repertoire managing and analysis
intersect
Intersection between sets of sequences or any elements.
vis.number.count
Plot a histogram of counts.
mitcr.stats
MiTCR data frame basic statistics.
segments.alphabets
Alphabets of V-J segments.
column.summary
Columns statistics.
get.all.substrings
Get all substrings for the given sequence.
find.similar.sequences
Find similar sequences.
vis.V.usage
Histogram of segments usage.
startmitcr
Start MiTCR directly from the package.
parse.folder
Parse all files to dataframes from the given path to folder.