Package: Cogito 1.13.0
Annika Bürger
Cogito: Compare genomic intervals tool - Automated, complete, reproducible and clear report about genomic and epigenomic data sets
Biological studies often consist of multiple conditions which are examined with different laboratory set ups like RNA-sequencing or ChIP-sequencing. To get an overview about the whole resulting data set, Cogito provides an automated, complete, reproducible and clear report about all samples and basic comparisons between all different samples. This report can be used as documentation about the data set or as starting point for further custom analysis.
Authors:
Cogito_1.13.0.tar.gz
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Cogito_1.13.0.tgz(r-4.4-any)Cogito_1.13.0.tgz(r-4.3-any)
Cogito_1.13.0.tar.gz(r-4.5-noble)Cogito_1.13.0.tar.gz(r-4.4-noble)
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Cogito.pdf |Cogito.html✨
Cogito/json (API)
| # Install 'Cogito' in R: |
| install.packages('Cogito', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org')) |
- MurEpi.ChIP.small - Example data set: Murine ChIP-seq data of GEO GSE77004
- MurEpi.RNA.small - Example data set: Murine RNA-seq RPKM values of GSE77004
- MurEpi.RRBS.small - Example data set: Murine methylation status data set of GSE77004
On BioConductor:Cogito-1.11.0(bioc 3.20)Cogito-1.10.0(bioc 3.19)
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
functionalgenomicsgeneregulationsoftwaresequencing
Last updated 23 days agofrom:55b1c5a6ed. Checks:OK: 2 ERROR: 5. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 30 2024 |
| R-4.5-win | ERROR | Oct 30 2024 |
| R-4.5-linux | OK | Oct 30 2024 |
| R-4.4-win | ERROR | Oct 30 2024 |
| R-4.4-mac | ERROR | Oct 30 2024 |
| R-4.3-win | ERROR | Oct 30 2024 |
| R-4.3-mac | ERROR | Oct 30 2024 |
Exports:aggregateRangessummarizeRanges
Dependencies:abindAnnotationDbiaskpassbase64encBHBiobaseBiocGenericsBiocIOBiocManagerBiocParallelBiostringsbitbit64bitopsblobbslibcachemclicodetoolscolorspacecpp11crayoncurlDBIDelayedArraydigestentropyevaluatefansifarverfastmapfontawesomeformatRfsfutile.loggerfutile.optionsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicFeaturesGenomicRangesggplot2gluegtablehighrhtmltoolshttrIRangesisobandjquerylibjsonliteKEGGRESTknitrlabelinglambda.rlatticelifecyclemagrittrMASSMatrixMatrixGenericsmatrixStatsmemoisemgcvmimemunsellnlmeopensslpillarpkgconfigplogrpngR6rappdirsRColorBrewerRCurlrestfulrRhtslibrjsonrlangrmarkdownRsamtoolsRSQLitertracklayerS4ArraysS4VectorssassscalessnowSparseArraySummarizedExperimentsystibbletinytexTxDb.Mmusculus.UCSC.mm9.knownGeneUCSC.utilsutf8vctrsviridisLitewithrxfunXMLXVectoryamlzlibbioc
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregate GRanges with columns of attached values to genes | aggregateRanges |
| Example data set: Murine ChIP-seq data of GEO GSE77004 | MurEpi.ChIP.small |
| Example data set: Murine RNA-seq RPKM values of GSE77004 | MurEpi.RNA.small |
| Example data set: Murine methylation status data set of GSE77004 | MurEpi.RRBS.small |
| Summarize Aggregated GRanges | summarizeRanges |
