vignettes/MicrobiomeBenchmarkData.Rmd
MicrobiomeBenchmarkData.RmdThe MicrobiomeBenchamrkData package provides access to a
collection of datasets with biological ground truth for benchmarking
differential abundance methods. The datasets are deposited on Zenodo: https://doi.org/10.5281/zenodo.6911026
## Install BioConductor if not installed
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
## Release version (not yet in Bioc, so it doesn't work yet)
BiocManager::install("MicrobiomeBenchmarkData")
## Development version
BiocManager::install("waldronlab/MicrobiomeBenchmarkData") All sample metadata is merged into a single data frame and provided as a data object:
data('sampleMetadata', package = 'MicrobiomeBenchmarkData')
## Get columns present in all samples
sample_metadata <- sampleMetadata |>
discard(~any(is.na(.x))) |>
head()
knitr::kable(sample_metadata)| dataset | sample_id | body_site | library_size | pmid | study_condition | sequencing_method |
|---|---|---|---|---|---|---|
| HMP_2012_16S_gingival_V13 | 700103497 | oral_cavity | 5356 | 22699609 | control | 16S |
| HMP_2012_16S_gingival_V13 | 700106940 | oral_cavity | 4489 | 22699609 | control | 16S |
| HMP_2012_16S_gingival_V13 | 700097304 | oral_cavity | 3043 | 22699609 | control | 16S |
| HMP_2012_16S_gingival_V13 | 700099015 | oral_cavity | 2832 | 22699609 | control | 16S |
| HMP_2012_16S_gingival_V13 | 700097644 | oral_cavity | 2815 | 22699609 | control | 16S |
| HMP_2012_16S_gingival_V13 | 700097247 | oral_cavity | 6333 | 22699609 | control | 16S |
Currently, there are 6 datasets available through the
MicrobiomeBenchmarkData. These datasets are accessed through the
getBenchmarkData function.
If no arguments are provided, the list of available datasets is printed on screen and a data.frame is returned with the description of the datasets:
dats <- getBenchmarkData()
#> 1 HMP_2012_16S_gingival_V13
#> 2 HMP_2012_16S_gingival_V35
#> 3 HMP_2012_16S_gingival_V35_subset
#> 4 HMP_2012_WMS_gingival
#> 5 Stammler_2016_16S_spikein
#> 6 Ravel_2011_16S_BV
#>
#> Use vignette('datasets', package = 'MicrobiomeBenchmarkData') for a detailed description of the datasets.
#>
#> Use getBenchmarkData(dryrun = FALSE) to import all of the datasets.
dats
#> Dataset Dimensions Body.site
#> 1 HMP_2012_16S_gingival_V13 33127 x 311 Gingiva
#> 2 HMP_2012_16S_gingival_V35 17949 x 311 Gingiva
#> 3 HMP_2012_16S_gingival_V35_subset 892 x 76 Gingiva
#> 4 HMP_2012_WMS_gingival 235 x 16 Gingiva
#> 5 Stammler_2016_16S_spikein 247 x 394 Stool
#> 6 Ravel_2011_16S_BV 4036 x 17 Vagina
#> Contrasts
#> 1 Subgingival vs Supragingival plaque.
#> 2 Subgingival vs Supragingival plaque.
#> 3 Subgingival vs Supragingival plaque.
#> 4 Subgingival vs Supragingival plaque.
#> 5 Pre-ASCT (allogeneic stem cell transplantation) vs 14 days after treatment.
#> 6 Healthy vs bacterial vaginosis
#> Biological.ground.truth
#> 1 Enrichment of aerobic taxa in the supragingival plaque and enrichment of anaerobic taxa in the subgingival plaque.
#> 2 Enrichment of aerobic taxa in the supragingival plaque and enrichment of anaerobic taxa in the subgingival plaque.
#> 3 Enrichment of aerobic taxa in the supragingival plaque and enrichment of anaerobic taxa in the subgingival plaque.
#> 4 Enrichment of aerobic taxa in the supragingival plaque and enrichment of anaerobic taxa in the subgingival plaque.
#> 5 Same bacterial loads of the spike-in bacteria across all samples: Salinibacter ruber (extreme halophilic), Rhizobium radiobacter (found in soils and plants), and Alicyclobacillus acidiphilu (thermo-acidophilic).
#> 6 Decrease of Lactobacillus and increase of bacteria isolated during bacterial vaginosis in samples with high Nugent scores (bacterial vaginosis).In order to import a dataset, the getBenchmarkData
function must be used with the name of the dataset as the first argument
(x) and the dryrun argument set to
FALSE. The output is a list vector with the dataset
imported as a TreeSummarizedExperiment object.
tse <- getBenchmarkData('HMP_2012_16S_gingival_V35_subset', dryrun = FALSE)[[1]]
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V35_subset_count_matrix.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V35_subset_taxonomy_table.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V35_subset_taxonomy_tree.newick'
#> Finished HMP_2012_16S_gingival_V35_subset.
tse
#> class: TreeSummarizedExperiment
#> dim: 892 76
#> metadata(0):
#> assays(1): counts
#> rownames(892): OTU_97.31247 OTU_97.44487 ... OTU_97.45365 OTU_97.45307
#> rowData names(7): kingdom phylum ... genus taxon_annotation
#> colnames(76): 700023057 700023179 ... 700114009 700114338
#> colData names(13): dataset subject_id ... sequencing_method
#> variable_region_16s
#> reducedDimNames(0):
#> mainExpName: NULL
#> altExpNames(0):
#> rowLinks: a LinkDataFrame (892 rows)
#> rowTree: 1 phylo tree(s) (892 leaves)
#> colLinks: NULL
#> colTree: NULLSeveral datasets can be imported simultaneously by giving the names of the different datasets in a character vector:
list_tse <- getBenchmarkData(dats$Dataset[2:4], dryrun = FALSE)
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V35_count_matrix.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V35_taxonomy_table.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V35_taxonomy_tree.newick'
#> Finished HMP_2012_16S_gingival_V35.
#> Finished HMP_2012_16S_gingival_V35_subset.
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_WMS_gingival_count_matrix.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_WMS_gingival_taxonomy_table.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_WMS_gingival_taxonomy_tree.newick'
#> Finished HMP_2012_WMS_gingival.
str(list_tse, max.level = 1)
#> List of 3
#> $ HMP_2012_16S_gingival_V35 :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ HMP_2012_16S_gingival_V35_subset:Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ HMP_2012_WMS_gingival :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slotsIf all of the datasets must to be imported, this can be done by
providing the dryrun = FALSE argument alone.
mbd <- getBenchmarkData(dryrun = FALSE)
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V13_count_matrix.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V13_taxonomy_table.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/HMP_2012_16S_gingival_V13_taxonomy_tree.newick'
#> Finished HMP_2012_16S_gingival_V13.
#> Finished HMP_2012_16S_gingival_V35.
#> Finished HMP_2012_16S_gingival_V35_subset.
#> Finished HMP_2012_WMS_gingival.
#> adding rname 'https://zenodo.org/record/6911027/files/Ravel_2011_16S_BV_count_matrix.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/Ravel_2011_16S_BV_taxonomy_table.tsv'
#> Warning: No taxonomy_tree available for Ravel_2011_16S_BV.
#> Finished Ravel_2011_16S_BV.
#> adding rname 'https://zenodo.org/record/6911027/files/Stammler_2016_16S_spikein_count_matrix.tsv'
#> adding rname 'https://zenodo.org/record/6911027/files/Stammler_2016_16S_spikein_taxonomy_table.tsv'
#> Warning: No taxonomy_tree available for Stammler_2016_16S_spikein.
#> Finished Stammler_2016_16S_spikein.
str(mbd, max.level = 1)
#> List of 6
#> $ HMP_2012_16S_gingival_V13 :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ HMP_2012_16S_gingival_V35 :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ HMP_2012_16S_gingival_V35_subset:Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ HMP_2012_WMS_gingival :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ Ravel_2011_16S_BV :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slots
#> $ Stammler_2016_16S_spikein :Formal class 'TreeSummarizedExperiment' [package "TreeSummarizedExperiment"] with 14 slotsThe biological annotations of each taxa are provided as a column in
the rowData slot of the TreeSummarizedExperiment.
## In the case, the column is named as taxon_annotation
tse <- mbd$HMP_2012_16S_gingival_V35_subset
rowData(tse)
#> DataFrame with 892 rows and 7 columns
#> kingdom phylum class order
#> <character> <character> <character> <character>
#> OTU_97.31247 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.44487 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.34979 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.34572 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.42259 Bacteria Firmicutes Bacilli Lactobacillales
#> ... ... ... ... ...
#> OTU_97.44294 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.45429 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.44375 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.45365 Bacteria Firmicutes Bacilli Lactobacillales
#> OTU_97.45307 Bacteria Firmicutes Bacilli Lactobacillales
#> family genus taxon_annotation
#> <character> <character> <character>
#> OTU_97.31247 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.44487 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.34979 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.34572 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.42259 Streptococcaceae Streptococcus facultative_anaerobic
#> ... ... ... ...
#> OTU_97.44294 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.45429 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.44375 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.45365 Streptococcaceae Streptococcus facultative_anaerobic
#> OTU_97.45307 Streptococcaceae Streptococcus facultative_anaerobicThe datasets are cached so they’re only downloaded once. The cache
and all of the files contained in it can be removed with the
removeCache function.
sessionInfo()
#> R version 4.3.0 (2023-04-21)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 22.04.2 LTS
#>
#> Matrix products: default
#> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.20.so; LAPACK version 3.10.0
#>
#> locale:
#> [1] LC_CTYPE=C.UTF-8 LC_NUMERIC=C LC_TIME=C.UTF-8
#> [4] LC_COLLATE=C.UTF-8 LC_MONETARY=C.UTF-8 LC_MESSAGES=C.UTF-8
#> [7] LC_PAPER=C.UTF-8 LC_NAME=C LC_ADDRESS=C
#> [10] LC_TELEPHONE=C LC_MEASUREMENT=C.UTF-8 LC_IDENTIFICATION=C
#>
#> time zone: UTC
#> tzcode source: system (glibc)
#>
#> attached base packages:
#> [1] stats4 stats graphics grDevices utils datasets methods
#> [8] base
#>
#> other attached packages:
#> [1] purrr_1.0.1 MicrobiomeBenchmarkData_1.3.0
#> [3] TreeSummarizedExperiment_2.8.0 Biostrings_2.68.0
#> [5] XVector_0.40.0 SingleCellExperiment_1.22.0
#> [7] SummarizedExperiment_1.30.0 Biobase_2.60.0
#> [9] GenomicRanges_1.52.0 GenomeInfoDb_1.36.0
#> [11] IRanges_2.34.0 S4Vectors_0.38.0
#> [13] BiocGenerics_0.46.0 MatrixGenerics_1.12.0
#> [15] matrixStats_0.63.0 BiocStyle_2.28.0
#>
#> loaded via a namespace (and not attached):
#> [1] xfun_0.39 bslib_0.4.2 lattice_0.21-8
#> [4] yulab.utils_0.0.6 vctrs_0.6.2 tools_4.3.0
#> [7] bitops_1.0-7 generics_0.1.3 curl_5.0.0
#> [10] parallel_4.3.0 RSQLite_2.3.1 tibble_3.2.1
#> [13] fansi_1.0.4 blob_1.2.4 pkgconfig_2.0.3
#> [16] Matrix_1.5-4 dbplyr_2.3.2 desc_1.4.2
#> [19] lifecycle_1.0.3 GenomeInfoDbData_1.2.10 compiler_4.3.0
#> [22] stringr_1.5.0 treeio_1.24.0 textshaping_0.3.6
#> [25] codetools_0.2-19 htmltools_0.5.5 sass_0.4.5
#> [28] lazyeval_0.2.2 RCurl_1.98-1.12 yaml_2.3.7
#> [31] tidyr_1.3.0 pkgdown_2.0.7 pillar_1.9.0
#> [34] crayon_1.5.2 jquerylib_0.1.4 BiocParallel_1.34.0
#> [37] DelayedArray_0.25.0 cachem_1.0.7 nlme_3.1-162
#> [40] tidyselect_1.2.0 digest_0.6.31 stringi_1.7.12
#> [43] dplyr_1.1.2 bookdown_0.33 rprojroot_2.0.3
#> [46] fastmap_1.1.1 grid_4.3.0 cli_3.6.1
#> [49] magrittr_2.0.3 utf8_1.2.3 ape_5.7-1
#> [52] withr_2.5.0 filelock_1.0.2 bit64_4.0.5
#> [55] httr_1.4.5 rmarkdown_2.21 bit_4.0.5
#> [58] ragg_1.2.5 memoise_2.0.1 evaluate_0.20
#> [61] knitr_1.42 BiocFileCache_2.8.0 rlang_1.1.0
#> [64] Rcpp_1.0.10 DBI_1.1.3 tidytree_0.4.2
#> [67] glue_1.6.2 BiocManager_1.30.20 jsonlite_1.8.4
#> [70] R6_2.5.1 systemfonts_1.0.4 fs_1.6.2
#> [73] zlibbioc_1.46.0