# 5. HPAanalyze use case: Export Human Protein Atlas (HPA) data as JSON

Anh N. Tran1*

1Northwestern University, Illinois, USA

* trannhatanh89@gmail.com

#### 6/8/2019

    library(BiocStyle)
    library(HPAanalyze)
    library(dplyr)
    library(jsonlite)

# 1 The case

In certain situation, users may want to export HPA downloaded data into JavaScript Object Notation (JSON) format to use for purposed such as asynchronous, real-time server-to-browser communication. To reduce package dependencies, `HPAanalyze` does not support exporting to JSON via the `hpaExport` function. However, this can be done using a short script as described below.

# 2 The solution

Exporting data to JSON can be achieved by converting dataframes resulting from `hpaDownload`/`hpaSubset` to JSON format using the `jsonlite` package and write the files to `.json` file.

## 2.1 Download and subset data

There is no special processing needed to the datasets. You can download and subset data as usual. The resulting object is a list of dataframes.

    data <- hpaDownload(downloadList = "histology", version = "example")
    data_subset <-
      hpaSubset(data,
                targetGene = c('TP53', 'EGFR', 'CD44', 'PTEN', 'IDH1'))

## 2.2 Convert dataframes to JSON

The list of dataframes will then be converted to a list of `json` using `jsonlite::toJSON`.

    data_json <- lapply(data_subset, jsonlite::toJSON)

    str(data_json)

    # List of 3
    #  $ normal_tissue       : 'json' chr "[{\"ensembl\":\"ENSG00000026508\",\"gene\":\"CD44\",\"tissue\":\"adrenal gland\",\"cell_type\":\"glandular cell"| __truncated__
    #  $ pathology           : 'json' chr "[{\"ensembl\":\"ENSG00000026508\",\"gene\":\"CD44\",\"cancer\":\"breast cancer\",\"high\":1,\"medium\":6,\"low\"| __truncated__
    #  $ subcellular_location: 'json' chr "[{\"ensembl\":\"ENSG00000026508\",\"gene\":\"CD44\",\"reliability\":\"Enhanced\",\"enhanced\":\"Golgi apparatus"| __truncated__

## 2.3 Write JSON file

Finally, the `.json` file can be saved to your working folder using the follow code. Notice that there will be one `.json` file for each dataset.

    for (i in seq_along(data_json)) {
      write(data_json[[i]],
            file = paste0("hpa_data_", names(data_json[i]), ".json"))
    }

# 3 In one function

If you routinely export HPA data into JSON format, the following function allow you to do so with the same syntax as `hpaExport`.

    ## The function (note that you don't need to put .json into the file name)
    hpaExportJSON <- function(data, fileName) {
      data_json <- lapply(data, jsonlite::toJSON)
      for (i in seq_along(data_json)) {
        write(data_json[[i]],
              file = paste0(fileName, "_", names(data_json[i]), ".json"))
      }
    }

    ## Export data subset
    hpaExportJSON(data_subset, fileName = "hpa_data")

# 4 Copyright

Anh Tran, 2018-2020

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