Package: MicrobiomeBenchmarkData 1.15.1

Samuel Gamboa

MicrobiomeBenchmarkData: Datasets for benchmarking in microbiome research

The MicrobiomeBenchmarkData package provides functionality to access microbiome datasets suitable for benchmarking. These datasets have some biological truth, which allows to have expected results for comparison. The datasets come from various published sources and are provided as TreeSummarizedExperiment objects. Currently, only datasets suitable for benchmarking differential abundance methods are available.

Authors:Samuel Gamboa [aut, cre], Levi Waldron [aut], Marcel Ramos [ctb], NCI [fnd]

MicrobiomeBenchmarkData_1.15.1.tar.gz
MicrobiomeBenchmarkData_1.15.1.zip(r-4.7-any)MicrobiomeBenchmarkData_1.15.1.zip(r-4.6-any)MicrobiomeBenchmarkData_1.15.1.zip(r-4.5-any)
MicrobiomeBenchmarkData_1.15.1.tgz(r-4.6-any)MicrobiomeBenchmarkData_1.15.1.tgz(r-4.5-any)
MicrobiomeBenchmarkData_1.15.1.tar.gz(r-4.7-any)MicrobiomeBenchmarkData_1.15.1.tar.gz(r-4.6-any)
MicrobiomeBenchmarkData_1.15.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MicrobiomeBenchmarkData/json (API)

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

Bug tracker:https://github.com/waldronlab/microbiomebenchmarkdata/issues

Pkgdown/docs site:https://waldronlab.io

Datasets:

On BioConductor:MicrobiomeBenchmarkData-1.15.1(data/experiment 3.24)MicrobiomeBenchmarkData-1.14.0(data/experiment 3.23)

experimentdatamicrobiomedatareproducibleresearchsequencingdatabioconductor-packager01ca230551

5.30 score 22 scripts 3 exports 75 dependencies

Last updated from:ed900aa65c. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE319
source / vignettesOK405
linux-releaseNOTE337
macos-releaseNOTE256
macos-oldrelNOTE211
windows-develNOTE282
windows-releaseNOTE266
windows-oldrelNOTE263
wasm-releaseOK148

Exports:getBenchmarkDataremoveCachescml

Dependencies:abindapeaskpassBHBiobaseBiocFileCacheBiocGenericsBiocParallelBiostringsbitbit64blobcachemclicodetoolscpp11crayoncurlDBIdbplyrDelayedArraydigestdplyrfastmapfilelockformatRfsfutile.loggerfutile.optionsgenericsGenomicRangesgluehttr2IRangesjsonlitelambda.rlatticelazyevallifecyclemagrittrMatrixMatrixGenericsmatrixStatsmemoisenlmeopensslpillarpkgconfigpurrrR6rappdirsRcpprlangRSQLiteS4ArraysS4VectorsSeqinfoSingleCellExperimentsnowSparseArraystringistringrSummarizedExperimentsystibbletidyrtidyselecttidytreetreeioTreeSummarizedExperimentutf8vctrswithrXVectoryulab.utils

Recalibration of the Stammler_2016_16S_spikein dataset
Import data | Ids of the spike-in bacteria | Recalibrate based on Salinibacter ruber abundance. | A more convenient way using the scml function included in the package: | Session information

Last update: 2024-09-02
Started: 2022-07-06

Datasets in MicrobiomeBenchmarkData

Last update: 2022-10-26
Started: 2021-09-24

MicrobiomeBenchmarkData
Introduction | Installation | Sample metadata | Accessing datasets | Print avaialable datasets | Access a single dataset | Access a few datasets | Access all of the datasets | Annotations for each taxa are included in rowData | Cache | Session information

Last update: 2022-10-26
Started: 2021-09-07

Readme and manuals

Help Manual

Help pageTopics
Get datasetgetBenchmarkData
MicrobiomeBenchmarkDataMicrobiomeBenchmarkData-package MicrobiomeBenchmarkData
Remove cacheremoveCache
sampleMetadatasampleMetadata
SCML: spike-in-based calibration to total microbial loadscml