HMP16SData: Efficient Access to the Human Microbiome Project Through Bioconductor

Abstract

Phase 1 of the Human Microbiome Project (HMP) investigated 18 body subsites of 242 healthy American adults to produce the first comprehensive reference for the composition and variation of the “healthy” human microbiome. Publicly available data sets from amplicon sequencing of two 16S ribosomal RNA variable regions, with extensive controlled-access participant data, provide a reference for ongoing microbiome studies. However, utilization of these data sets can be hindered by the complex bioinformatic steps required to access, import, decrypt, and merge the various components in formats suitable for ecological and statistical analysis. The HMP16SData package provides count data for both 16S ribosomal RNA variable regions, integrated with phylogeny, taxonomy, public participant data, and controlled participant data for authorized researchers, using standard integrative Bioconductor data objects. By removing bioinformatic hurdles of data access and management, HMP16SData enables epidemiologists with only basic R skills to quickly analyze HMP data.

Editor’s note: An invited commentary on this article appears on page 1027, and the authors’ response appears on page 1031.

The Human Microbiome Project (HMP) was one of the first large-scale population studies of microbiome variation outside of disease, including healthy American adults aged 18–40 years and producing a comprehensive reference for the composition and variation of the “healthy” human microbiome (1, 2). Raw and processed 16S ribosomal RNA (16S) and metagenomic shotgun (MGX) sequencing data can be freely downloaded from the HMP Data Analysis and Coordinating Center (DACC) or analyzed online using the HMP data portal (3, 4).

However, accessing and analyzing the data with statistical software still involves substantial bioinformatic and data management challenges. These include data import and merging of microbiome profiles with public and controlled-access participant data, integration with phylogenetic trees, potentially mapping microbial and participant identifiers for comparison between 16S and MGX data sets, and accessing controlled participant data.

We thus developed the HMP16SData (5) R/Bioconductor package (R Foundation for Statistical Computing, Vienna, Austria, and Huber et al. (6)) to simplify access to and analysis of HMP 16S data. The design of the package follows our curatedMetagenomicData R/Bioconductor package (7), enabling comparative analysis with MGX samples from the HMP and dozens of other studies. HMP16SData leverages Bioconductor’s ExperimentHub and the SummarizedExperiment (6) data class to distribute merged taxonomic and public-access participant data. It provides 16S gene sequencing data for variable regions 1–3 (V13) and 3–5 (V35), with merged participant data, and a function for automated merging of controlled-access participant data to researchers with a project approved by the National Center for Biotechnology Information (NCBI) Database of Genotypes and Phenotypes (dbGaP). Methods for efficient subsetting and coercion to the phyloseq class, which is used by the phyloseq package for comparative ecological and differential abundance analyses (8), are also provided. Finally, HMP16SData greatly simplifies access to and merging of restricted participant data. These simplifications enable epidemiologists with only basic R skills and limited knowledge of HMP DACC or dbGaP procedures to quickly make use of the HMP data.

METHODS

HMP16SData provides data from the HMP 16S compendium as processed through the HMP DACC QIIME pipeline (9, 10). The “data-raw” package subdirectory provides all download and merging code for HMP DACC data; we noted slightly lower numbers available than originally reported (2). All publicly available participant data, as obtained from the HMP DACC, is also included, and a function provides simplified access to and merging of controlled data from dbGaP for registered researchers. Use of HMP16SData begins with one of two functions: V13 (to download data for 16S V13) or V35 (to download data for 16S V35), each of which returns a SummarizedExperiment object. Each object contains data/metadata (with specific accessors) as follows: experiment-level metadata (metadata), sample-level metadata (colData), sequencing count data (assay), phylogenetic classification data (rowData), and a phylogenetic tree (metadata). Selection of samples according to body site, visit number, and taxonomic hierarchy is straightforward through standard SummarizedExperiment or phyloseq subsetting methods. Researchers with an approved dbGaP project can optionally use a second function, attach_dbGaP, to attach controlled participant data, prior to coercion to a phyloseq object for ecological analyses such as alpha and beta diversity. Figure 1 demonstrates the selection of only stool samples, attachment of controlled participant data, and coercion to a phyloseq object. Additional examples are provided in the HMP16SData package vignette, and complete function documentation is available in the reference manual.

Figure 1.

Data access using HMP16SData. This example demonstrates subsetting by body subsite, attaching controlled participant data from the Database of Genotypes and Phenotypes, and coercion to a phyloseq (8) class object.

Controlled-access participant data analysis

Access to most participant data is controlled, requiring authorization through the National Center for Biotechnology Information dbGaP, and requires the use of specialized software for download and decryption. Specifically, nonrestricted participant data include only visit number, sex, run center, body site, and body subsite; an additional 248 participant data variables are available through dbGaP after project registration. The process involves making a controlled-access application through dbGaP for HMP Core Microbiome Sampling Protocol A (HMP-A) (phs000228.v4.p1)—see the HMP16SData package vignette for specific details. After project approval, dbGaP provides researchers with a “repository key” that identifies and decrypts controlled-access participant data. The attach_dbGaP function takes the public SummarizedExperiment data set provided by HMP16SData and the path to the dbGaP repository key as arguments; it performs download, decryption, and merging of controlled participant data, and returns another SummarizedExperiment with controlled-access participant data added to its colData slot. Internally, attach_dbGaP uses system calls to the National Center for Biotechnology Information Sequence Read Archive (SRA) Toolkit for download and decryption, and R functionality to load and merge the controlled data. A data dictionary describing the controlled-access participant data variables is incorporated into the package and is accessible by entering data(dictionary).

Phyloseq class coercion

The phyloseq package is a commonly used tool for ecological analysis of microbiome data in R/Bioconductor. HMP16SData provides a function, as_phyloseq, to coerce its default SummarizedExperiment objects to phyloseq objects. The resulting objects contain taxonomic abundance count data, participant data, complete taxonomy, and phylogenetic trees, enabling computation of UniFrac (11) and other ecological distances.

RESULTS

HMP16SData provides a total of 7,641 taxonomic profiles from 16S variable regions 1–3 and 3–5 for 239 participants in the HMP whose microbiome profiles could be mapped to participant data (see the “data-raw” package directory for download and merging code), for 18 body subsites and up to 3 visits. The two variable regions, V13 and V35, identified 43,140 and 45,383 taxonomic clades, respectively, with resolution down to the genus level at a median sequencing depth of 4,428 reads per specimen. These profiles are provided as two Bioconductor SummarizedExperiment class objects: V13 and V35 (Table 1), which integrate operational taxonomic unit count data, taxonomy, a phylogenetic tree, and public-use participant information. Each object includes both 16S and MGX sample identifiers, enabling mapping and comparison with MGX profiles distributed by our curatedMetagenomicData R/Bioconductor package (7). Such a comparison is illustrated in the phylum-level relative abundance plots of matched 16S and MGX sequencing samples in Web Figure 1 (available at https://academic.oup.com/aje). Code to reproduce Table 1 and Web Figure 1 are provided in the HMP16SData package vignette documentation along with additional analysis examples, and the color palette used in Web Figure 1 is optimized for color-blind individuals as proposed by Wong (12).

Table 1.

Selected Characteristics of 16S Ribosomal RNA Samples for Variable Regions 1–3 and 3–5 Available Through HMP16SData

Characteristic	V13		V35
	No.a	%	No.a	%
Sex
Female	1,521	52.48	2,188	46.13
Male	1,377	47.52	2,555	53.87
HMP body subsite
Tongue dorsum	190	6.56	316	6.66
Supragingival plaque	189	6.52	313	6.60
Right retroauricular crease	187	6.45	297	6.26
Stool	187	6.45	319	6.73
Left retroauricular crease	186	6.42	285	6.01
Palatine tonsils	186	6.42	312	6.58
Buccal mucosa	183	6.31	312	6.58
Subgingival plaque	183	6.31	309	6.51
Attached keratinized gingiva	181	6.25	313	6.60
Hard palate	178	6.14	302	6.37
Throat	170	5.87	307	6.47
Saliva	162	5.59	290	6.11
Anterior nares	161	5.56	269	5.67
Right antecubital fossa	146	5.04	207	4.36
Left antecubital fossa	145	5.00	201	4.24
Mid vagina	89	3.07	133	2.80
Posterior fornix	88	3.04	133	2.80
Vaginal introitus	87	3.00	125	2.64

Abbreviations: HMP, Human Microbiome Project; V13, variable regions 1–3; V35, variable regions 3–5.

^a All numbers represent samples rather than subjects, given that there were multiple samples per subject.

DISCUSSION

The HMP provides a comprehensive reference for the composition, diversity, and variation of the human microbiome in the absence of overt disease, making it a potential control or comparison cohort for many microbiome studies. The R/Bioconductor environment provides an extensive range of operations for data analysis, with documented workflows (13) available for typical microbiome investigations. The HMP16SData package thus integrates HMP 16S taxonomic abundance profiles, controlled-access and public participant data, and phylogenetic distances with R/Bioconductor. This greatly reduces the time and bioinformatics expertise required to analyze these data, particularly in the context of additional integrated microbiome population studies. Further, users of other analysis environments can easily export the data to other formats (SAS (SAS Institute, Inc., Cary, North Carolina), SPSS (SPSS, Inc., Chicago, Illinois), Stata (StataCorp LLC, College Station, Texas), etc.), using the haven R package (14); see the HMP16SData package vignette for specific details. We hope this facilitates broader utilization of the data generated by the HMP among epidemiologists, statisticians, and computational biologists.

Some precautions should be noted when using HMP16SData in comparative metagenomic analyses. First, studies of the human microbiome are susceptible to batch effects, which should be accounted for in making cross-study comparisons, along with other forms of technical variation (15, 16). Second, the V13 and V35 data sets are obtained from sequencing different variable regions of the 16S ribosomal RNA gene, and provide correlated but different estimates of taxonomic relative abundance (17, 18). In the case of the HMP, the samples sequenced in V13 are a subset of those that were sequenced in V35. The two variable regions differ in their ability to distinguish specific microbial clades (e.g., V13 is preferred for discriminating streptococci). Users should choose the better region for their purposes based on the comparison with MGX sequencing provided by Supplemental Figure 3 of the original Human Microbiome Project publication (1) or by the more thorough technical evaluation of the HMP 16S data sets provided by the Jumpstart Consortium (19).

The number of sequence reads per specimen varies according to body site and specimen, from a maximum of 151,000 reads from a single specimen to a minimum of 1 read. HMP16SData retains all available data, but most analyses should include a quality control step of removing specimens with very low sequencing depth caused by amplification failure or lack of microbial DNA in the specimen. For example, 14% of skin specimens have fewer than 100 V35 reads, compared with only 4% for V13 reads.

Finally, users of these data should be aware that the HMP data were generated using a legacy platform and processing pipelines. The samples from 15 (male) or 18 (female) body sites of phenotyped adults between the ages of 18 and 40 years who passed a screening for systemic health based on oral, cutaneous, and body mass exclusion criteria were sequenced on the Roche 454 FLX Titanium platform (2). The platform is no longer used, and the software pipelines (QIIME version 1.3 and mothur version 1.1.8) used to produce operational-taxonomic-unit tables have since been updated significantly (10, 20). As such, cross-study analysis of differential abundance or clustering requires care and attention to the biases arising from these differences, particularly when comparing with data produced by more recent sequencing platforms and software pipelines. These data, however, remain a key reference for the general structure of the “healthy” human microbiome.

With these precautions in mind, this resource is intended to provide a key reference data set for the general structure of the “healthy” human microbiome. It enables efficient access to and analysis of the HMP by greatly reducing previous hurdles of data access and management. Finally, while we have simplified the use of the legacy HMP data, we also understand the need to reprocess the raw sequencing data through contemporary bioinformatics tools and will seek to do so in the future.

Abbreviations

16S

16S ribosomal RNA

DACC

Data Analysis and Coordinating Center

dbGaP

Database of Genotypes and Phenotypes

HMP

Human Microbiome Project

MGX

metagenomic shotgun

V13

variable regions 1–3

V35

variable regions 3–5