Package: ramr 1.15.1
Oleksii Nikolaienko
ramr: Detection of Rare Aberrantly Methylated Regions in Array and NGS Data
ramr is an R package for detection of epimutations (i.e., infrequent aberrant DNA methylation events) in large data sets obtained by methylation profiling using array or high-throughput methylation sequencing. In addition, package provides functions to visualize found aberrantly methylated regions (AMRs), to generate sets of all possible regions to be used as reference sets for enrichment analysis, and to generate biologically relevant test data sets for performance evaluation of AMR/DMR search algorithms.
Authors:
ramr_1.15.1.tar.gz
ramr_1.15.1.zip(r-4.5)ramr_1.15.1.zip(r-4.4)ramr_1.15.1.zip(r-4.3)
ramr_1.15.1.tgz(r-4.4-any)ramr_1.15.1.tgz(r-4.3-any)
ramr_1.15.1.tar.gz(r-4.5-noble)ramr_1.15.1.tar.gz(r-4.4-noble)
ramr_1.15.1.tgz(r-4.4-emscripten)ramr_1.15.1.tgz(r-4.3-emscripten)
ramr.pdf |ramr.html✨
ramr/json (API)
NEWS
| # Install 'ramr' in R: |
| install.packages('ramr', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/bbcg/ramr/issues
- ramr.data - Simulated Illumina HumanMethylation 450k data set with 3000 CpGs and 100 samples
- ramr.samples - Simulated Illumina HumanMethylation 450k data set with 3000 CpGs and 100 samples
- ramr.tp.nonunique - Simulated Illumina HumanMethylation 450k data set with 3000 CpGs and 100 samples
- ramr.tp.unique - Simulated Illumina HumanMethylation 450k data set with 3000 CpGs and 100 samples
On BioConductor:ramr-1.15.0(bioc 3.21)ramr-1.14.0(bioc 3.20)
dnamethylationdifferentialmethylationepigeneticsmethylationarraymethylseqaberrant-methylationbioconductordna-methylationepimutationmethylation-microarraysnext-generation-sequencing
Last updated 4 days agofrom:4e3b57e0e9. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Dec 19 2024 |
| R-4.5-win | NOTE | Dec 19 2024 |
| R-4.5-linux | NOTE | Dec 19 2024 |
| R-4.4-win | NOTE | Dec 19 2024 |
| R-4.4-mac | NOTE | Dec 19 2024 |
| R-4.3-win | NOTE | Dec 19 2024 |
| R-4.3-mac | NOTE | Dec 19 2024 |
Exports:getAMRgetUniverseplotAMRsimulateAMRsimulateData
Dependencies:askpassBiocGenericsclicodetoolscolorspacecurldata.tabledigestdoParalleldoRNGEnvStatsExtDistfansifarverforeachgamlssgamlss.datagamlss.distgenericsGenomeInfoDbGenomeInfoDbDataGenomicRangesggplot2gluegtablehttrIRangesisobanditeratorsjsonlitelabelinglatticelifecyclemagrittrMASSMatrixmatrixStatsmgcvmimemunsellnlmenloptrnortestnumDerivopenssloptimxpillarpkgconfigpracmaR6RColorBrewerrlangrngtoolsS4VectorsscalessurvivalsystibbleUCSC.utilsutf8vctrsviridisLitewithrXVectorzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Search for aberrantly methylated regions | getAMR |
| Merges, filters and outputs all genomic regions of a given `GRanges` object | getUniverse |
| Plot aberrantly methylated regions | plotAMR |
| Simulated Illumina HumanMethylation 450k data set with 3000 CpGs and 100 samples | ramr.data ramr.samples ramr.tp.nonunique ramr.tp.unique |
| Simulate a set of aberrantly methylated regions | simulateAMR |
| Template-based simulation of methylation data sets | simulateData |
