curatedMetagenomicData

The curatedMetagenomicData package provides standardized, curated human microbiome data for novel analyses. It includes gene families, marker abundance, marker presence, pathway abundance, pathway coverage, and relative abundance for samples collected from different body sites. The bacterial, fungal, and archaeal taxonomic abundances for each sample were calculated with MetaPhlAn3, and metabolic functional potential was calculated with HUMAnN3. The manually curated sample metadata and standardized metagenomic data are available as (Tree)SummarizedExperiment objects.

Installation

To install curatedMetagenomicData from Bioconductor, use BiocManager as follows.

BiocManager::install("curatedMetagenomicData")

To install curatedMetagenomicData from GitHub, use BiocManager as follows.

BiocManager::install("waldronlab/curatedMetagenomicData", dependencies = TRUE, build_vignettes = TRUE)

Most users should simply install curatedMetagenomicData from Bioconductor.

Examples

To access curated metagenomic data, users will use the curatedMetagenomicData() method both to query and return resources. Multiple resources can be queried or returned with a single call to curatedMetagenomicData(), but only the titles of resources are returned by default.

curatedMetagenomicData("AsnicarF_20.+")
## 2021-03-31.AsnicarF_2017.gene_families
## 2021-03-31.AsnicarF_2017.marker_abundance
## 2021-03-31.AsnicarF_2017.marker_presence
## 2021-03-31.AsnicarF_2017.pathway_abundance
## 2021-03-31.AsnicarF_2017.pathway_coverage
## 2021-03-31.AsnicarF_2017.relative_abundance
## 2021-10-14.AsnicarF_2017.gene_families
## 2021-10-14.AsnicarF_2017.marker_abundance
## 2021-10-14.AsnicarF_2017.marker_presence
## 2021-10-14.AsnicarF_2017.pathway_abundance
## 2021-10-14.AsnicarF_2017.pathway_coverage
## 2021-10-14.AsnicarF_2017.relative_abundance
## 2021-03-31.AsnicarF_2021.gene_families
## 2021-03-31.AsnicarF_2021.marker_abundance
## 2021-03-31.AsnicarF_2021.marker_presence
## 2021-03-31.AsnicarF_2021.pathway_abundance
## 2021-03-31.AsnicarF_2021.pathway_coverage
## 2021-03-31.AsnicarF_2021.relative_abundance

When the dryrun argument is set to FALSE, a list of SummarizedExperiment and/or TreeSummarizedExperiment objects is returned. The rownames argument determines the type of rownames to use for relative_abundance resources: either "long" (the default), "short" (species name), or "NCBI" (NCBI Taxonomy ID). When a single resource is requested, a single element list is returned.

curatedMetagenomicData("AsnicarF_2017.relative_abundance", dryrun = FALSE, rownames = "short")
## $`2021-10-14.AsnicarF_2017.relative_abundance`
## class: TreeSummarizedExperiment 
## dim: 296 24 
## metadata(1): agglomerated_by_rank
## assays(1): relative_abundance
## rownames(296): Escherichia coli Bifidobacterium bifidum ...
##   Streptococcus gordonii Abiotrophia sp. HMSC24B09
## rowData names(7): superkingdom phylum ... genus species
## colnames(24): MV_FEI1_t1Q14 MV_FEI2_t1Q14 ... MV_MIM5_t2M14
##   MV_MIM5_t3F15
## colData names(22): study_name subject_id ... lactating curator
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):
## rowLinks: a LinkDataFrame (296 rows)
## rowTree: 1 phylo tree(s) (10430 leaves)
## colLinks: NULL
## colTree: NULL

When the counts argument is set to TRUE, relative abundance proportions are multiplied by read depth and rounded to the nearest integer prior to being returned. Also, when multiple resources are requested, the list will contain named elements corresponding to each SummarizedExperiment and/or TreeSummarizedExperiment object.

curatedMetagenomicData("AsnicarF_20.+.relative_abundance", dryrun = FALSE, counts = TRUE, rownames = "short")
## $`2021-10-14.AsnicarF_2017.relative_abundance`
## class: TreeSummarizedExperiment 
## dim: 296 24 
## metadata(1): agglomerated_by_rank
## assays(1): relative_abundance
## rownames(296): Escherichia coli Bifidobacterium bifidum ...
##   Streptococcus gordonii Abiotrophia sp. HMSC24B09
## rowData names(7): superkingdom phylum ... genus species
## colnames(24): MV_FEI1_t1Q14 MV_FEI2_t1Q14 ... MV_MIM5_t2M14
##   MV_MIM5_t3F15
## colData names(22): study_name subject_id ... lactating curator
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):
## rowLinks: a LinkDataFrame (296 rows)
## rowTree: 1 phylo tree(s) (10430 leaves)
## colLinks: NULL
## colTree: NULL
## 
## $`2021-03-31.AsnicarF_2021.relative_abundance`
## class: TreeSummarizedExperiment 
## dim: 633 1098 
## metadata(1): agglomerated_by_rank
## assays(1): relative_abundance
## rownames(633): Phocaeicola vulgatus Bacteroides stercoris ...
##   Pyramidobacter sp. C12-8 Brevibacterium aurantiacum
## rowData names(7): superkingdom phylum ... genus species
## colnames(1098): SAMEA7041133 SAMEA7041134 ... SAMEA7045952 SAMEA7045953
## colData names(24): study_name subject_id ... family treatment
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):
## rowLinks: a LinkDataFrame (633 rows)
## rowTree: 1 phylo tree(s) (10430 leaves)
## colLinks: NULL
## colTree: NULL

Analyses

See curatedMetagenomicAnalyses for analyses in R and Python using curatedMetagenomicData.

Contributing

To contribute to the curatedMetagenomicData R/Bioconductor package, first read the contributing guidelines and then open an issue. Also, note that in contributing you agree to abide by the code of conduct.

Pasolli E, Schiffer L, Manghi P, Renson A, Obenchain V, Truong D, Beghini F, Malik F, Ramos M, Dowd J, Huttenhower C, Morgan M, Segata N, Waldron L (2017). Accessible, curated metagenomic data through ExperimentHub. Nat. Methods, 14 (11), 1023-1024. ISSN 1548-7091, 1548-7105, doi: 10.1038/nmeth.4468.