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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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Version

Install

install.packages('tcR')

Monthly Downloads

2

Version

1.0

License

Apache License 2.0

Maintainer

Vadim Nazarov

Last Published

December 12th, 2014

Functions in tcR (1.0)

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.