HMP16SData is a
Bioconductor ExperimentData package of the Human Microbiome Project
(HMP) 16S rRNA sequencing data for variable regions 1–3 and 3–5. Raw
data files are provided in the package as downloaded from the HMP Data
Analysis and Coordination Center.
Processed data is provided as SummarizedExperiment class objects via
ExperimentHub.
HMP16SData can be installed using BiocManager as follows.
BiocManager::install("HMP16SData")Once installed,
HMP16SData
provides two functions to access data – one for variable region 1–3 and
another for variable region 3–5. When called, as follows, the functions
will download data from an
ExperimentHub
Amazon S3 (Simple Storage Service) bucket over https or load data from
a local cache.
V13()## class: SummarizedExperiment
## dim: 43140 2898
## metadata(2): experimentData phylogeneticTree
## assays(1): 16SrRNA
## rownames(43140): OTU_97.1 OTU_97.10 ... OTU_97.9997 OTU_97.9999
## rowData names(7): CONSENSUS_LINEAGE SUPERKINGDOM ... FAMILY GENUS
## colnames(2898): 700013549 700014386 ... 700114963 700114965
## colData names(7): RSID VISITNO ... HMP_BODY_SUBSITE SRS_SAMPLE_ID
V35()## class: SummarizedExperiment
## dim: 45383 4743
## metadata(2): experimentData phylogeneticTree
## assays(1): 16SrRNA
## rownames(45383): OTU_97.1 OTU_97.10 ... OTU_97.9998 OTU_97.9999
## rowData names(7): CONSENSUS_LINEAGE SUPERKINGDOM ... FAMILY GENUS
## colnames(4743): 700013549 700014386 ... 700114717 700114750
## colData names(7): RSID VISITNO ... HMP_BODY_SUBSITE SRS_SAMPLE_ID
The two data sets are represented as SummarizedExperiment objects, a
standard Bioconductor class that is amenable to subsetting and analysis.
To maintain brevity, details of the SummarizedExperiment class are not
outlined here but the
SummarizedExperiment
package provides an excellent vignette.
For a complete explanation of the features of HMP16SData, see the package vignette or read the American Journal of Epidemiology article.
Schiffer, L. et al. HMP16SData: Efficient Access to the Human Microbiome Project through Bioconductor. Am. J. Epidemiol. (2019).
Griffith, J. C. & Morgan, X. C. Invited Commentary: Improving accessibility of the Human Microbiome Project data through integration with R/Bioconductor. Am. J. Epidemiol. (2019).
Waldron, L. et al. Improving Accessibility of the Human Microbiome Project Data Through Integration With R/Bioconductor. Am. J. Epidemiol. (2019).