Package 'oglcnac'

Compare Two Atlas Tables

Description

Summarizes added, removed, and shared Atlas row IDs.

Usage

compare_atlas_tables(old_data, new_data, id_col = "id")

Arguments

old_data	Previous Atlas data frame.
new_data	Updated Atlas data frame.
id_col	Row identifier column. Defaults to "id".

Value

A one-row data frame with row and ID counts.

---

Compare Input and Updated Tibbles

Description

This function compares the original input tibble and the updated tibble, identifying and reporting any changes in the specified columns ('entry_name', 'protein_name', 'gene_name').

Usage

compare_tibbles_uniprot(
  original_tibble,
  updated_tibble,
  entry_name_col = "entry_name",
  protein_name_col = "protein_name",
  gene_name_col = "gene_name"
)

Arguments

original_tibble	The original tibble before processing.
updated_tibble	The tibble returned after processing.
entry_name_col	The column name for entry names (default: "entry_name").
protein_name_col	The column name for protein names (default: "protein_name").
gene_name_col	The column name for gene names (default: "gene_name").

Value

None. Prints the differences between the tibbles.

Examples

# Example usage:

# Original input tibble
input_data <- tibble::tibble(
  id = c(1, 2),
  species = c("mouse", "rat"),
  sample_type = c("brain", "liver"),
  accession = c("O88737", "Q9R064"),
  accession_source = c("UniProt", "UniProt")
)

# Process the tibble (this will add the entry_name, protein_name, and gene_name)
processed_data <- process_tibble_uniprot(input_data)

# Compare the original and processed tibbles
compare_tibbles_uniprot(input_data, processed_data)

---

Export O-GlcNAcAtlas Data as CSV

Description

Writes a validated Atlas table to CSV with blank cells for missing values.

Usage

export_atlas_csv(data, file, dataset = NULL)

Arguments

data	A data frame containing Atlas records.
file	Output CSV path.
dataset	Optional dataset label: "unambiguous" or "ambiguous".

Value

The output file path, invisibly.

---

Launch oglcnac Shiny App

Description

This function launches a Shiny App for uploading, processing, and downloading UniProt data in CSV, TSV, or Excel format. Users can upload data, preview it, and select specific columns for processing. The processed data can be viewed and downloaded.

Usage

launch_app()

Value

None

Examples

if (interactive()) {
  oglcnac::launch_app()
}

---

Parse UniProt Data

Description

This function parses the data retrieved from the UniProt API to extract the entry name, protein name, and gene name.

Usage

parse_uniprot_data(uniprot_data)

Arguments

uniprot_data

A list returned by the UniProt API query.

Value

A list containing 'entry_name', 'protein_name', and 'gene_name'.

Examples

# Example usage:

# Retrieve UniProt data
test_result <- retrieve_uniprot_data("O88737")

# Parse the UniProt data
parsed_result <- parse_uniprot_data(test_result)

# Print the parsed result
print(parsed_result)

---

Prepare O-GlcNAcAtlas Data for Export

Description

Adds or normalizes the ambiguous field used by the public static website.

Usage

prepare_atlas_data(data, dataset = NULL)

Arguments

data	A data frame containing Atlas records.
dataset	Optional dataset label: "unambiguous" or "ambiguous".

Value

A data frame ready to export.

---

Process a Tibble of UniProt Data

Description

This function processes a tibble containing accession and accession_source columns. It retrieves data from the UniProt API for rows with accession_source == "UniProt" and overwrites or creates the entry_name, protein_name, and gene_name columns only if the parsed values are not NULL or NA.

Usage

process_tibble_uniprot(
  data,
  accession_col = "accession",
  accession_source_col = "accession_source",
  entry_name_col = "entry_name",
  protein_name_col = "protein_name",
  gene_name_col = "gene_name"
)

Arguments

data	A tibble containing at least accession and accession_source columns.
accession_col	The column name for accession numbers (default: "accession").
accession_source_col	The column name for accession sources (default: "accession_source").
entry_name_col	The column name for entry names (default: "entry_name").
protein_name_col	The column name for protein names (default: "protein_name").
gene_name_col	The column name for gene names (default: "gene_name").

Value

A tibble with UniProt data processed.

Examples

# Example usage:

# Load necessary library
library(tibble)

# Reduced example data as an R tibble
test_data <- tibble::tibble(
  id = c(1, 78, 83, 87),
  species = c("mouse", "mouse", "rat", "mouse"),
  sample_type = c("brain", "brain", "brain", "brain"),
  accession = c("O88737", "O35927", "Q9R064", "P51611"),
  accession_source = c("OtherDB", "UniProt", "UniProt", "UniProt"),
  entry_name = c("BSN_MOUSE", NA, "GORS2_RAT", NA),
  protein_name = c("Protein bassoon", NA, "Golgi reassembly-stacking protein2", NA),
  gene_name = c("Bsn", NA, "Gorasp2", NA)
)

# Process the tibble
result_data <- process_tibble_uniprot(test_data)

# Compare the original and processed tibbles
compare_tibbles_uniprot(test_data, result_data)

---

Process UniProt Data with a Local Cache

Description

Enriches a data frame like process_tibble_uniprot() while avoiding repeated UniProt requests for accessions already present in a local RDS cache.

Usage

process_tibble_uniprot_cached(
  data,
  cache_path = NULL,
  accession_col = "accession",
  accession_source_col = "accession_source",
  entry_name_col = "entry_name",
  protein_name_col = "protein_name",
  gene_name_col = "gene_name"
)

Arguments

data	A data frame containing accession and accession source columns.
cache_path	Optional RDS file path for cached parsed UniProt records.
accession_col	The accession column name.
accession_source_col	The accession source column name.
entry_name_col	The entry name column name.
protein_name_col	The protein name column name.
gene_name_col	The gene name column name.

Value

A data frame with UniProt fields filled where available.

---

Retrieve Data from UniProt API

Description

This function sends a GET request to the UniProt REST API and retrieves data based on the provided UniProt accession number.

Usage

retrieve_uniprot_data(accession)

Arguments

accession

A character string representing the UniProt accession number.

Value

A list containing the retrieved data in JSON format, or NULL if the request fails.

Examples

# Example usage

result <- retrieve_uniprot_data("O88737")
print(result)

---

Validate O-GlcNAcAtlas Data

Description

Checks that an Atlas table has the columns needed by the public website and that dataset labels are not mixed accidentally.

Usage

validate_atlas_data(data, dataset = NULL)

Arguments

data	A data frame containing Atlas records.
dataset	Optional dataset label: "unambiguous" for dataset-I or "ambiguous" for dataset-II.

Value

A list with valid, errors, warnings, and summary.

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