In Bioconductor:
- Background: The Human Protein Atlas program aims to map human proteins via multiple technologies including imaging, proteomics and transcriptomics.
- Results:
HPAanalyzeis an R package for retreiving and performing exploratory data analysis from HPA. It provides functionality for importing data tables and xml files from HPA, exporting and visualizing data, as well as download all staining images of interest. The package is free, open source, and available via Github. - Conclusions:
HPAanalyzeintergrates into the R workflow via thetidyversephilosophy and data structures, and can be used in combination with Bioconductor packages for easy analysis of HPA data. - Citation: Tran, A.N., Dussaq, A.M., Kennell, T. et al. HPAanalyze: an R package that facilitates the retrieval and analysis of the Human Protein Atlas data. BMC Bioinformatics 20, 463 (2019) https://doi.org/10.1186/s12859-019-3059-z
The Human Protein Atlas (HPA) is a comprehensive resource for exploration of human proteome which contains a vast amount of proteomics and transcriptomics data generated from antibody-based tissue micro-array profiling and RNA deep-sequencing.
The program has generated protein expression profiles in human normal tissues with cell type-specific expression patterns, cancer and cell lines via an innovative immunohistochemistry-based approach. These profiles are accompanied by a large collection of high quality histological staining images, annotated with clinical data and quantification. The database also includes classification of protein into both functional classes (such as transcription factors or kinases) and project-related classes (such as candidate genes for cancer). Starting from version 4.0, the HPA includes subcellular location profiles generated based on confocal images of immunofluorescent stained cells. Together, these data provide a detailed picture of protein expression in human cells and tissues, facilitating tissue-based diagnostis and research.
Data from the HPA are freely available via proteinatlas.org, allowing scientists to access and incorporate the data into their research. Here, we introduce HPAanalyze, an R package aims to simplify exploratory data analysis from those data.
HPAanalyze is designed to fullfill 3 main tasks: (1) Import, subsetting and export downloadable datasets; (2) Visualization of downloadable datasets for exploratory analysis; and (3) Working with the individual XML files. This package aims to serve researchers with little programming experience, but also allow power users to use the imported data as desired.
The stable version of HPAanalyze should be downloaded from Bioconductor:
if (!requireNamespace("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("HPAanalyze")The development version of HPAanalyze is available on Github can be installed with:
devtools::install_github("anhtr/HPAanalyze")The hpaDownload() function downloads full datasets from HPA and
imports them into R as a list of tibbles, the standard object of
tidyverse, which can subsequently be subset with hpaSubset() and
export into .xmlx files with hpaExport(). The standard object allow
the imported data to be further processed in a traditional R workflow.
The ability to quickly subset and export data gives researchers the
option to use other non-R downstream tools, such as GraphPad for
creating publication-quality graphics, or share a subset of data
containing only proteins of interest.
The hpaVis function family take the output of hpaDownload() (or
hpaSubset()) provides quick visualization of the data, with the
intention of aiding exploratory analysis. Nevertheless, the standard
ggplot object output of these functions give users the option to
further customize the plots for publication. All hpaVis functions
share the same syntax for arguments: subsetting, specifying colors and
opting to use custom themes.
The first release of the HPAanalyze package includes three functions:
hpaVisTissue() for the normal tissue, hpaVisPatho() for the
pathology/cancer, and hpaVisSubcell() for the subcellular location
datasets.
The hpaXml function family import and extract data from individual XML
entries from HPA. The hpaXmlGet() function downloads and imports data
as “xml_document”/“xml_node” object, which can subsequently be processed
by other hpaXml functions. The XML format from HPA contains a wealth
of information that may not be covered by this package. However, users
can extract any data of interest from the imported XML file using the
xml2 package.
In the first release, HPAanalyze includes four functions for data
extraction from HPA XML files: hpaXmlProtClass() for protein class
information, hpaTissueExprSum() for summary of protein expression in
tissue, hpaXmlAntibody() for a list of antibody used to stain for the
protein of interest, and hpaTissueExpr() for a detailed data from each
sample including clinical data and IHC scoring.
hpaTissueExprSum and hpaTissueExpr provide download links to
download relevant staining images, with the former function also gives
the options to automate the downloading process.
- Project name: HPAanalyze
- Project home page: https://github.com/anhtr/HPAanalyze
- Operating system(s): All platforms where R is available, including Windows, Linux, OS X
- Other requirements: R 3.5.0 or higher, and the R packages dplyr, openxlsx, ggplot2, tibble, xml2, stats, utils, gridExtra
- License: GPL-3
We appreciate the support of the National institutes of Health National Cancer Institute R01 CA151522 and funds from the Department of Cell, Developmental and Integrative Biology at the University of Alabama at Birmingham.
Anh Tran, 2018-2023
Please cite: Tran, A.N., Dussaq, A.M., Kennell, T. et al. HPAanalyze: an R package that facilitates the retrieval and analysis of the Human Protein Atlas data. BMC Bioinformatics 20, 463 (2019) https://doi.org/10.1186/s12859-019-3059-z