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tcR (version 1.1)

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')

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Version

1.1

License

Apache License 2.0

Maintainer

Vadim Nazarov

Last Published

January 10th, 2015

Functions in tcR (1.1)

get.all.substrings

Get all substrings for the given sequence.

entropy

Information measures.

permutedf

Shuffling data frames.

AA_TABLE

Tables with genetic code.

reverse.string

Reverse given character vector by the given n-plets.

get.deletions.alpha

Compute the number of deletions in MiTCR data frames.

rarefaction

Diversity evaluation using rarefaction.

generate.tcr

Generate random nucleotide TCR sequences.

check.distribution

Check for adequaty of distrubution.

startmitcr

Start MiTCR directly from the package.

gc.content

GC-content of a nucleotide sequences.

beta.prob

List with assembling probabilities of beta chain TCRs.

set.rank

Set new columns "Rank" and "Index".

contamination.stats

Contamination filtering.

mitcr.stats

MiTCR data frame basic statistics.

inverse.simpson

Distribution evaluation.

revcomp

DNA reverse complementing and translation.

parse.file.list

Parse files from the given vector or list with filepaths and return list with data.frames.

intersect

Intersection between sets of sequences or any elements.

top.cross

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

parse.file

Parse input file with the given filename to a data frame.

get.inframes

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

barcodes.to.reads

Rearrange columns with counts for clonesets.

find.clonotypes

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

set.pb

Simple functions for manipulating progress bars.

vis.heatmap

Heatmap.

codon.variants

Functions for working with aminoacid sequences.

entropy.seg

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

freq.segments

V- and J-segments frequency.

apply.symm

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

convergence.index

Compute convergence characteristics of repertoires.

bootstrap.tcr

Bootstrap for data frames in package tcR.

generate.kmers

Generate k-mers.

cosine.similarity

Set and vector similarity measures.

vis.pca

PCA result visualisation

vis.top.proportions

Visualisation of top clones proportions.

Get a sample from matrix with probabilities.

gibbs.sampler

Gibbs Sampler.

get.n.barcodes

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

shared.repertoire

Shared TCR repertoire managing and analysis

top.fun

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

spectratyping

Spectratype plot.

twinsdata

Twins alpha-beta chain data

segments.list

Segment data.

vis.V.usage

Histogram of segments usage.

pca.segments

Perform PCA on segments frequency data.

assymetry

Normalised log assymetry.

segments.alphabets

Alphabets of V-J segments.

vis.number.count

Plot a histogram of counts.

sample.clones

Get a random subset from a data.frame.

tailbound.proportion

Proportions of specifyed subsets of clones.

find.similar.sequences

Find similar sequences.

vis.kmer.histogram

Plot of the most frequent kmers.

has.class

Check if a given object has a given class.

vis.count.len

Plot a histogram of lengths.

vis.rarefaction

Rarefaction statistics visualisation.

vis.clonal.dynamics

Visualise clonal dynamics among time points.

get.kmers

Get kmers from sequences.

kmer.table

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

kmer.profile

Profile of sequences of equal length.

parse.folder

Parse all files to dataframes from the given path to folder.

matrixdiagcopy

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

cosine.sharing

Shared repertoire analysis.

vis.radarlike

Radar-like / spider-like plots.

vis.group.boxplot

Boxplot for groups of observations.