Package: TRONCO 2.45.0

Luca De Sano

TRONCO: TRONCO, an R package for TRanslational ONCOlogy

The TRONCO (TRanslational ONCOlogy) R package collects algorithms to infer progression models via the approach of Suppes-Bayes Causal Network, both from an ensemble of tumors (cross-sectional samples) and within an individual patient (multi-region or single-cell samples). The package provides parallel implementation of algorithms that process binary matrices where each row represents a tumor sample and each column a single-nucleotide or a structural variant driving the progression; a 0/1 value models the absence/presence of that alteration in the sample. The tool can import data from plain, MAF or GISTIC format files, and can fetch it from the cBioPortal for cancer genomics. Functions for data manipulation and visualization are provided, as well as functions to import/export such data to other bioinformatics tools for, e.g, clustering or detection of mutually exclusive alterations. Inferred models can be visualized and tested for their confidence via bootstrap and cross-validation. TRONCO is used for the implementation of the Pipeline for Cancer Inference (PICNIC).

Authors:Marco Antoniotti [ctb], Giulio Caravagna [aut], Luca De Sano [cre, aut], Alex Graudenzi [aut], Giancarlo Mauri [ctb], Bud Mishra [ctb], Daniele Ramazzotti [aut]

TRONCO_2.45.0.tar.gz
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manual.pdf |manual.html
DESCRIPTION |NEWS
card.svg |card.png
TRONCO/json (API)

# Install 'TRONCO' in R:
install.packages('TRONCO', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/bimib-disco/tronco/issues

Datasets:

On BioConductor:TRONCO-2.45.0(bioc 3.24)TRONCO-2.44.0(bioc 3.23)

biomedicalinformaticsbayesiangraphandnetworksomaticmutationnetworkinferencenetworkclusteringdataimportsinglecellimmunooncologyalgorithmscancer-inferencetumors

8.42 score 30 stars 45 scripts 2 mentions 106 exports 38 dependencies

Last updated from:652830a9fc. Checks:1 WARNING, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING191
linux-devel-x86_64OK293
source / vignettesOK256
linux-release-x86_64OK253
macos-release-arm64OK171
macos-oldrel-arm64OK210
windows-develOK219
windows-releaseOK246
windows-oldrelOK213
wasm-releaseOK169

Exports:ANDannotate.descriptionannotate.stagesas.adj.matrixas.alterationsas.bootstrap.scoresas.colorsas.conditional.probsas.confidenceas.descriptionas.eventsas.events.in.patternsas.events.in.sampleas.geneas.genesas.genes.in.patternsas.genotypesas.hypothesesas.joint.probsas.kfold.elossas.kfold.posterras.kfold.prederras.marginal.probsas.modelsas.parametersas.pathwayas.patternsas.samplesas.selective.advantage.relationsas.stagesas.typesas.types.in.patternschange.colorconsolidate.datadelete.eventdelete.genedelete.hypothesisdelete.modeldelete.patterndelete.samplesdelete.typeduplicatesebindenforce.numericenforce.stringevents.selectionexport.graphmlexport.mutexexport.nbs.inputextract.MAF.HuGO.Entrez.mapgenes.table.reporthas.duplicateshas.modelhas.stageshypothesis.addhypothesis.add.grouphypothesis.add.homologousimport.genotypesimport.GISTICimport.MAFimport.modelimport.mutex.groupsintersect.datasetsis.compliantjoin.eventsjoin.typeskeysToNamesnameToKeyneventsngenesnhypothesesnpatternsnsamplesntypesoncoprintoncoprint.cbioORorder.frequencypathway.visualizationpheatmaprank.recurrentsrename.generename.typesamples.selectionsbindssplitTCGA.map.clinical.dataTCGA.multiple.samplesTCGA.remove.multiple.samplesTCGA.shorten.barcodestrimtronco.bootstraptronco.capresetronco.capritronco.chowliutronco.edmondstronco.gabowtronco.kfold.elosstronco.kfold.posterrtronco.kfold.prederrtronco.pattern.plottronco.plottronco.primviewwhich.samplesXOR

Dependencies:BiocGenericsbnlearncirclizeclicodetoolscolorspacecpp11doParallelfarverforeachgenericsGlobalOptionsgluegraphgridExtragtablegtoolsigraphiteratorslabelinglatticelifecyclemagrittrMatrixpkgconfigR.matlabR.methodsS3R.ooR.utilsR6RColorBrewerRgraphvizrlangscalesshapevctrsviridisLitextable

An introduction to the TRONCO R package
Changelog | Algorithms and useful links | External links to resources related to TRONCO

Last update: 2024-09-29
Started: 2023-04-05

Data manipulation
Modifying events and samples | Modifying patterns | Subsetting a dataset

Last update: 2024-09-29
Started: 2023-04-05

Data visualization
Summary report for a dataset and boolean queries | Creating views with the as functions | Dataset size | Oncoprints | Groups visualization (e.g., pathways)

Last update: 2024-09-29
Started: 2023-04-05

Import/export from other tools

Last update: 2024-09-29
Started: 2023-04-05

Loading data
Preliminaries | Mutations annotated in a MAF format | Copy Number Variants annotated in the GISTIC format | Custom alterations annotated in a boolean matrix | Downloading data from the cBio portal for cancer genomics

Last update: 2024-09-29
Started: 2023-04-05

Model inference
Data consolidation. | CAPRI | Testable hypotheses via logical formulas (i.e., patterns) | Adding custom hypotheses. | Adding (automatically) hypotheses for homologous events. | Adding (automatically) hypotheses for a group of genes. | Querying, visualizing and manipulating CAPRI's patterns. | How to build a pattern. | Model reconstruction | CAPRESE | Directed Minimum Spanning Tree with Mutual Information | Partially Directed Minimum Spanning Tree with Mutual Information | Undirected Minimum Spanning Tree with Likelihood-Fit | Undirected Minimum Spanning Tree with Mutual Information

Last update: 2024-09-29
Started: 2023-04-05

Post reconstruction
Visualizing a reconstructed model | Accessing information within a model (e.g., confidence) | Model structure | Empirical probabilities | Confidence measures | Confidence via non-parametric and statistical bootstrap | Confidence via cross-validation (entropy loss, prediction and posterior classification errors)

Last update: 2024-09-29
Started: 2023-04-05

Readme and manuals

Help Manual

Help pageTopics
Atypical chronic myeloid leukemia datasetaCML
ANDAND
annotate.descriptionannotate.description
annotate.stagesannotate.stages
as.adj.matrixas.adj.matrix
as.alterationsas.alterations
as.bootstrap.scoresas.bootstrap.scores
as.colorsas.colors
as.conditional.probsas.conditional.probs
as.confidenceas.confidence
as.descriptionas.description
as.eventsas.events
as.events.in.patternsas.events.in.patterns
as.events.in.sampleas.events.in.sample
as.geneas.gene
as.genesas.genes
as.genes.in.patternsas.genes.in.patterns
as.genotypesas.genotypes
as.hypothesesas.hypotheses
as.joint.probsas.joint.probs
as.kfold.elossas.kfold.eloss
as.kfold.posterras.kfold.posterr
as.kfold.prederras.kfold.prederr
as.marginal.probsas.marginal.probs
as.modelsas.models
as.parametersas.parameters
as.pathwayas.pathway
as.patternsas.patterns
as.samplesas.samples
as.selective.advantage.relationsas.selective.advantage.relations
as.stagesas.stages
as.typesas.types
as.types.in.patternsas.types.in.patterns
change.colorchange.color
consolidate.dataconsolidate.data
GISTIC example datacrc_gistic
MAF example datacrc_maf
Plain mutation datasetcrc_plain
delete.eventdelete.event
delete.genedelete.gene
delete.hypothesisdelete.hypothesis
delete.modeldelete.model
delete.patterndelete.pattern
delete.samplesdelete.samples
delete.typedelete.type
duplicatesduplicates
ebindebind
enforce.numericenforce.numeric
enforce.stringenforce.string
events.selectionevents.selection
export.graphmlexport.graphml
export,mutexexport.mutex
export.nbs.inputexport.nbs.input
extract.MAF.HuGO.Entrez.mapextract.MAF.HuGO.Entrez.map
genes.table.reportgenes.table.report
has.duplicateshas.duplicates
has.modelhas.model
has stageshas.stages
hypothesis addhypothesis.add
hypothesis add grouphypothesis.add.group
hypothesis.add.homologoushypothesis.add.homologous
import.genotypesimport.genotypes
import.GISTICimport.GISTIC
import.MAFimport.MAF
import.modelimport.model
import.mutex.groupsimport.mutex.groups
intersect.datasetsintersect.datasets
is.compliantis.compliant
join.eventsjoin.events
join.typesjoin.types
keysToNameskeysToNames
MAF example datamaf
Simple mutation datasetmuts
nameToKeynameToKey
neventsnevents
ngenesngenes
Return the number of hypotheses in the datasetnhypotheses
Return the number of patterns in the datasetnpatterns
nsamplesnsamples
ntypesntypes
oncoprintoncoprint
oncoprint.cbiooncoprint.cbio
OROR
order.frequencyorder.frequency
pathway.visualizationpathway.visualization
A function to draw clustered heatmaps.pheatmap
rank.recurrentsrank.recurrents
rename.generename.gene
rename.typerename.type
samples.selectionsamples.selection
sbindsbind
ssplitssplit
Stage information for test_datasetstage
TCGA.map.clinical.dataTCGA.map.clinical.data
TCGA.multiple.samplesTCGA.multiple.samples
TCGA.remove.multiple.samplesTCGA.remove.multiple.samples
TCGA.shorten.barcodesTCGA.shorten.barcodes
A complete dataset with hypothesestest_dataset
A complete datasettest_dataset_no_hypos
A complete dataset with a reconstructed modeltest_model
A complete dataset with a reconstructed model and crossvalidation informationstest_model_kfold
trimtrim
tronco bootstraptronco.bootstrap
tronco capresetronco.caprese
tronco capritronco.capri
Tronco Chow Liutronco.chowliu
Tronco Edmondstronco.edmonds
Tronco Gabowtronco.gabow
tronco.kfold.elosstronco.kfold.eloss
tronco.kfold.posterr. For details and examples regarding the statistical assesment of an inferred model, we refer to the Vignette Section 7.tronco.kfold.posterr
tronco.kfold.prederrtronco.kfold.prederr
tronco.pattern.plottronco.pattern.plot
tronco.plottronco.plot
Tronco Primtronco.prim
viewview
which.sampleswhich.samples
XORXOR