Package: Melissa 1.28.0

C. A. Kapourani

Melissa: Bayesian clustering and imputationa of single cell methylomes

Melissa is a Baysian probabilistic model for jointly clustering and imputing single cell methylomes. This is done by taking into account local correlations via a Generalised Linear Model approach and global similarities using a mixture modelling approach.

Authors:C. A. Kapourani [aut, cre]

Melissa_1.28.0.tar.gz
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manual.pdf |manual.html✨
card.svg |card.png
Melissa/json (API)
NEWS

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

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

immunooncologydnamethylationgeneexpressiongeneregulationepigeneticsgeneticsclusteringfeatureextractionregressionrnaseqbayesiankeggsequencingcoveragesinglecell

4.08 score 10 scripts 291 downloads 4 mentions 13 exports 87 dependencies

Last updated from:abafc9a709 (on RELEASE_3_23). Checks:1 ERROR, 9 OK. Indexed: no.

TargetResultTimeFilesSyslog
bioc-checksERROR220
linux-devel-x86_64OK284
source / vignettesOK333
linux-release-x86_64OK269
macos-release-arm64OK149
macos-oldrel-arm64OK142
windows-develOK182
windows-releaseOK177
windows-oldrelOK175
wasm-releaseOK127

Exports:binarise_filescreate_melissa_data_objeval_cluster_performanceeval_imputation_performancefilter_by_coverage_across_cellsfilter_by_cpg_coveragefilter_by_variabilityimpute_met_filesimpute_test_metmelissamelissa_gibbspartition_datasetplot_melissa_profiles

Dependencies:assertthatbase64encBiocGenericsBiocManagerBiocStylebitopsbookdownBPRMethbslibcachemcaToolsclassclicodacodetoolscowplotcpp11data.tabledigestdoParallele1071earthevaluatefarverfastmapfontawesomeforeachFormulafsgenericsGenomicRangesggplot2gluegplotsgtablegtoolshighrhtmltoolsIRangesisobanditeratorsjquerylibjsonlitekernlabKernSmoothknitrlabelinglatticelifecyclemagrittrMASSMatrixmatrixcalcMatrixModelsmclustmcmcMCMCpackmemoisemimemvtnormplotmoplotrixproxyquantregR6randomForestrappdirsRColorBrewerRcppRcppArmadillorlangrmarkdownROCRS4VectorsS7sassscalesSeqinfoSparseMsurvivaltinytextruncnormvctrsviridisLitewithrxfunyaml

Process and filter scBS-seq data

Andreas C. Kapourani, Guido Sanguinetti

Rendered fromprocess_files.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2020-06-10
Started: 2019-02-15

Cluster and impute scBS-seq data using Melissa

Andreas C. Kapourani, Guido Sanguinetti

Rendered fromrun_melissa.Rmdusingknitr::rmarkdownon May 25 2026.

Last update: 2020-06-10
Started: 2019-02-15