TRONCO, an R package for TRanslational ONCOlogy


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Documentation for package ‘TRONCO’ version 2.2.0

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A C D E G H I K M N O P R S T W X

TRONCO-package TRONCO is a R package which collects algorithms to infer progression models from Bernoulli 0/1 profiles of genomic alterations across a tumor sample. Such profiles are usually visualized as a binary input matrix where each row represents a patient’s sample (e.g., the result of a sequenced tumor biopsy), and each column an event relevant to the progression (a certain type of somatic mutation, a focal or higher-level chromosomal copy number alteration, etc.); a 0/1 value models the absence/presence of that alteration in the sample. In this version of TRONCO such profiles can be readily imported by boolean matrices and MAF or GISTIC files. The package provides various functions to editing, visualize and subset such data, as well as functions to query the cBioPortal for cancer genomics. In the current version, TRONCO provides parallel implementations of CAPRESE [PLoS ONE 9(12): e115570] and CAPRI [Bioinformatics, doi:10.1093/bioinformatics/btv296] algorithms to infer progression models arranged as trees or general direct acyclic graphs. Bootstrap procedures to assess the non-prametric and statistical confidence of the inferred models are also provided. The package comes with example data available, which include the dataset of Atypical Chronic Myeloid Leukemia samples by Piazza et al., Nat. Genet., 45 (2013).

-- A --

aCML Atypical chronic myeloid leukemia dataset
AND AND
annotate.description annotate.description
annotate.stages annotate.stages
as.adj.matrix as.adj.matrix
as.alterations as.alterations
as.colors as.colors
as.conditional.probs as.conditional.probs
as.confidence as.confidence
as.description as.description
as.events as.events
as.events.in.patterns as.events.in.patterns
as.events.in.sample as.events.in.sample
as.events.test as events matrix
as.gene as.gene
as.genes as.genes
as.genes.in.patterns as.genes.in.patterns
as.genotypes as.genotypes
as.genotypes.test as genotypes matrix
as.hypotheses as.hypotheses
as.joint.probs as.joint.probs
as.marginal.probs as.marginal.probs
as.models as.models
as.pathway as.pathway
as.patterns as.patterns
as.samples as.samples
as.selective.advantage.relations as.selective.advantage.relations
as.stages as.stages
as.stages.test as stages matrix
as.types as.types
as.types.in.patterns as.types.in.patterns

-- C --

cbio.query cbio.query
change.color change.color
consolidate.data consolidate.data

-- D --

delete.event delete.event
delete.gene delete.gene
delete.hypothesis delete.hypothesis
delete.model delete.model
delete.pattern delete.pattern
delete.samples delete.samples
delete.type delete.type
duplicates duplicates

-- E --

ebind ebind
enforce.numeric enforce.numeric
enforce.string enforce.string
events.selection events.selection
export.mutex export,mutex
export.nbs.input export.nbs.input
extract.MAF.HuGO.Entrez.map extract.MAF.HuGO.Entrez.map

-- G --

genes.table.plot genes.table.plot
genes.table.report genes.table.report
gistic GISTIC example data

-- H --

has.duplicates has.duplicates
has.model has.model
has.stages has stages
hypothesis.add hypothesis add
hypothesis.add.group hypothesis add group
hypothesis.add.homologous hypothesis.add.homologous

-- I --

import.genotypes import.genotypes
import.GISTIC import.GISTIC
import.MAF import.MAF
import.mutex.groups import.mutex.groups
intersect.datasets intersect.datasets
is.compliant is.compliant

-- K --

keysToNames keysToNames

-- M --

maf MAF example data
merge.events merge.events
merge.types merge.types
muts Simple mutation dataset

-- N --

nevents nevents
ngenes ngenes
nhypotheses Return the number of hypotheses in the dataset
npatterns Return the number of patterns in the dataset
nsamples nsamples
ntypes ntypes

-- O --

oncoprint oncoprint
oncoprint.cbio oncoprint.cbio
OR OR

-- P --

pathway.visualization pathway.visualization
pheatmap A function to draw clustered heatmaps.

-- R --

rank.recurrents rank.recurrents
rename.gene rename.gene
rename.type rename.type

-- S --

samples.selection samples.selection
sbind sbind
show show
sort.by.frequency sort.by.frequency
ssplit ssplit
stage Stage information for test_dataset

-- T --

TCGA.map.clinical.data TCGA.map.clinical.data
TCGA.multiple.samples TCGA.multiple.samples
TCGA.remove.multiple.samples TCGA.remove.multiple.samples
TCGA.shorten.barcodes TCGA.shorten.barcodes
test_dataset A complete dataset with hypotheses
test_dataset_no_hypos A complete dataset
test_model A complete dataset with a reconstructed model
trim trim
TRONCO TRONCO is a R package which collects algorithms to infer progression models from Bernoulli 0/1 profiles of genomic alterations across a tumor sample. Such profiles are usually visualized as a binary input matrix where each row represents a patient’s sample (e.g., the result of a sequenced tumor biopsy), and each column an event relevant to the progression (a certain type of somatic mutation, a focal or higher-level chromosomal copy number alteration, etc.); a 0/1 value models the absence/presence of that alteration in the sample. In this version of TRONCO such profiles can be readily imported by boolean matrices and MAF or GISTIC files. The package provides various functions to editing, visualize and subset such data, as well as functions to query the cBioPortal for cancer genomics. In the current version, TRONCO provides parallel implementations of CAPRESE [PLoS ONE 9(12): e115570] and CAPRI [Bioinformatics, doi:10.1093/bioinformatics/btv296] algorithms to infer progression models arranged as trees or general direct acyclic graphs. Bootstrap procedures to assess the non-prametric and statistical confidence of the inferred models are also provided. The package comes with example data available, which include the dataset of Atypical Chronic Myeloid Leukemia samples by Piazza et al., Nat. Genet., 45 (2013).
tronco.bootstrap tronco bootstrap
tronco.caprese tronco caprese
tronco.capri tronco capri
tronco.plot tronco.plot

-- W --

which.samples which.samples

-- X --

XOR XOR