protti (version 0.9.0)

fetch_alphafold_aligned_error: Fetch AlphaFold aligned error

Description

Fetches the aligned error for AlphaFold predictions for provided proteins. The aligned error is useful for assessing inter-domain accuracy. In detail it represents the expected position error at residue x (scored residue), when the predicted and true structures are aligned on residue y (aligned residue).

Usage

fetch_alphafold_aligned_error(
  uniprot_ids = NULL,
  error_cutoff = 20,
  timeout = 30,
  max_tries = 1,
  return_data_frame = FALSE,
  show_progress = TRUE
)

Value

A list that contains aligned errors for AlphaFold predictions. If return_data_frame is TRUE, a data frame with this information is returned instead. The data frame contains the following columns:

• scored_residue: The error for this position is calculated based on the alignment to the aligned residue.

• aligned_residue: The residue that is aligned for the calculation of the error of the scored residue

• error: The predicted aligned error computed by alpha fold.

• accession: The UniProt protein identifier.

Arguments

uniprot_ids

a character vector of UniProt identifiers for which predictions should be fetched.

error_cutoff

a numeric value specifying the maximum position error (in Angstroms) that should be retained. setting this value to a low number reduces the size of the retrieved data. Default is 20.

timeout

a numeric value specifying the time in seconds until the download times out. The default is 30 seconds.

max_tries

a numeric value that specifies the number of times the function tries to download the data in case an error occurs. The default is 1.

return_data_frame

a logical value; if TRUE a data frame instead of a list is returned. It is recommended to only use this if information for few proteins is retrieved. Default is FALSE.

show_progress

a logical value; if TRUE a progress bar will be shown. Default is TRUE.

Examples

# \donttest{
aligned_error <- fetch_alphafold_aligned_error(
  uniprot_ids = c("F4HVG8", "O15552"),
  error_cutoff = 5,
  return_data_frame = TRUE
)

head(aligned_error, n = 10)
# }