README.Rmd

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output: github_document
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# HMP16SData

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`r BiocStyle::Biocpkg("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](https://tinyurl.com/y7ev836z). Processed data is provided as `SummarizedExperiment` class objects via `r BiocStyle::Biocpkg("ExperimentHub")`.

`r BiocStyle::Biocpkg("HMP16SData")` can be installed using `r BiocStyle::CRANpkg("BiocManager")` as follows.

```{r, eval = FALSE}
BiocManager::install("HMP16SData")
```

Once installed, `r BiocStyle::Biocpkg("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 `r BiocStyle::Biocpkg("ExperimentHub")` Amazon S3 (Simple Storage Service) bucket over `https` or load data from a local cache.

```{r, include = FALSE}
library(HMP16SData)
```

```{r, message = FALSE}
V13()
```

```{r, message = FALSE}
V35()
```

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 `r BiocStyle::Biocpkg("SummarizedExperiment")` package provides an excellent vignette.

For a complete explanation of the features of `r BiocStyle::Biocpkg("HMP16SData")`, see the [package vignette](https://tinyurl.com/yaob5n77) or read the [American Journal of Epidemiology article](https://tinyurl.com/y2o9x257).

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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).