Package: CIMICE 1.21.0

Nicolò Rossi

CIMICE: CIMICE-R: (Markov) Chain Method to Inferr Cancer Evolution

CIMICE is a tool in the field of tumor phylogenetics and its goal is to build a Markov Chain (called Cancer Progression Markov Chain, CPMC) in order to model tumor subtypes evolution. The input of CIMICE is a Mutational Matrix, so a boolean matrix representing altered genes in a collection of samples. These samples are assumed to be obtained with single-cell DNA analysis techniques and the tool is specifically written to use the peculiarities of this data for the CMPC construction.

Authors:Nicolò Rossi [aut, cre]

CIMICE_1.21.0.tar.gz
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CIMICE_1.21.0.tgz(r-4.6-any)CIMICE_1.21.0.tgz(r-4.5-any)
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CIMICE_1.21.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
CIMICE/json (API)
NEWS

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

Bug tracker:https://github.com/redsnic/cimice/issues

On BioConductor:CIMICE-1.21.0(bioc 3.24)CIMICE-1.20.0(bioc 3.23)

softwarebiologicalquestionnetworkinferenceresearchfieldphylogeneticsstatisticalmethodgraphandnetworktechnologysinglecell

4.30 score 5 scripts 340 downloads 50 exports 81 dependencies

Last updated from:57344c846b. Checks:8 NOTE, 2 OK. Indexed: yes.

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source / vignettesOK212
linux-release-x86_64NOTE297
macos-release-arm64NOTE263
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wasm-releaseOK144

Exports:annotate_mutational_matrixbinary_radix_sortbuild_subset_graphbuild_topology_subsetchunk_readercompact_datasetcompute_weights_defaultcomputeDWNWcomputeUPWcorrplot_from_mutational_matrixcorrplot_genescorrplot_samplesdataset_preprocessingdataset_preprocessing_populationdraw_ggraphdraw_networkD3draw_visNetworkexample_datasetexample_dataset_withFreqsfinalize_generatorfix_clonal_genotypeformat_labelsgene_mutations_histget_no_of_childrengraph_non_transitive_subset_topologymake_datasetmake_generator_stubmake_labelsnormalizeDWNWnormalizeUPWperturb_datasetplot_generatorprepare_generator_edge_set_commandprepare_labelsquick_runreadread_CAPRIread_CAPRI_stringread_CAPRIpopread_CAPRIpop_stringread_MAFread_matrixremove_transitive_edgessample_mutations_histselect_genes_on_mutationsselect_samples_on_mutationsset_generator_edgessimulate_generatorto_dotupdate_df

Dependencies:assertthatbase64encbslibcachemclicpp11data.tabledata.treedigestDNAcopydplyrevaluateexpmfarverfastmapfontawesomefsgenericsggcorrplotggforceggplot2ggraphggrepelgluegraphlayoutsgridExtragtablehighrhtmltoolshtmlwidgetsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemaftoolsmagrittrMASSMatrixmemoisemimenetworkD3pheatmappillarpkgconfigplyrpolyclippurrrR6rappdirsRColorBrewerRcppRcppArmadilloreshape2RhtslibrlangrmarkdownS7sassscalesstringistringrsurvivalsystemfontstibbletidygraphtidyrtidyselecttinytextweenrutf8vctrsviridisviridisLitevisNetworkwithrxfunyaml

CIMICE-R: (Markov) Chain Method to Infer Cancer Evolution

Nicolò Rossi

Rendered fromCIMICER.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2022-03-12
Started: 2021-08-03

Quick guide

Nicolò Rossi

Rendered fromCIMICE_SHORT.Rmdusingknitr::rmarkdownon May 29 2026.

Last update: 2021-07-07
Started: 2020-11-24

Readme and manuals

Help Manual

Help pageTopics
Add samples and genes names to a mutational matrixannotate_mutational_matrix
Radix sort for a binary matrixbinary_radix_sort
Remove transitive edges and prepare graphbuild_subset_graph
Compute subset relation as edge listbuild_topology_subset
Gradually read a file from diskchunk_reader
CIMICE PackageCIMICE
Compact dataset rowscompact_dataset
Compute default weightscompute_weights_default
Down weights computationcomputeDWNW
Down weights computation (aux)computeDWNW_aux
Up weights computationcomputeUPW
Up weights computation (aux)computeUPW_aux
Correlation plot from mutational matrixcorrplot_from_mutational_matrix
Gene based correlation plotcorrplot_genes
Sample based correlation plotcorrplot_samples
Run CIMICE preprocessingdataset_preprocessing
Run CIMICE preprocessing for poulation format datasetdataset_preprocessing_population
ggplot graph outputdraw_ggraph
NetworkD3 graph outputdraw_networkD3
VisNetwork graph output (default)draw_visNetwork
Creates a simple example datasetexample_dataset
Creates a simple example dataset with frequency columnexample_dataset_withFreqs
Finalize generator normalizing edge weightsfinalize_generator
Manage Clonal genotype in datafix_clonal_genotype
Format labels for output objectformat_labels
Histogram of genes' frequenciesgene_mutations_hist
Get number of childrenget_no_of_children
Default preparation of graph topologygraph_non_transitive_subset_topology
Dataset line by line construction: initializationmake_dataset
Create a stub for a generatormake_generator_stub
Helper function to create labelsmake_labels
Down weights normalizationnormalizeDWNW
Up weights normalizationnormalizeUPW
Perturbate a boolean matrixperturb_dataset
Plot a generatorplot_generator
Prepare a command to add edge weights to a generatorprepare_generator_edge_set_command
Prepare node labels based on genotypesprepare_labels
Run CIMICE defaultsquick_run
Read a "CAPRI" fileread
Read a "CAPRI" fileread_CAPRI
Read "CAPRI" file from a stringread_CAPRI_string
Read a "CAPRIpop" fileread_CAPRIpop
Read "CAPRIpop" file from a stringread_CAPRIpop_string
Create mutational matrix from MAF fileread_MAF
Read dataset from an R matrixread_matrix
Remove transitive edges from an edgelistremove_transitive_edges
Histogram of samples' frequenciessample_mutations_hist
Filter dataset by genes' mutation countselect_genes_on_mutations
Filter dataset by samples' mutation countselect_samples_on_mutations
Add edge weights to a generatorset_generator_edges
Create datasets from generatorssimulate_generator
Dot graph outputto_dot
Dataset line by line construction: add a sampleupdate_df