predatoR: Mutation impact Prediction

In berkgurdamar/predatoR: Mutation Impact Prediction Based on Network Properties

Mutation impact Prediction

Description

Main function for mutation impact prediction

Usage

predatoR(
  info_df,
  PDB_path = NULL,
  n_threads = NULL,
  gene_name_info = TRUE,
  distance_cutoff = 5,
  network_approach = "all"
)

Arguments

info_df	data.frame containing 'PDB_ID', 'Chain', 'Position', 'Reference Amino Acid', 'Mutated Amino Acid' and 'Gene_Name' (optional) information respectively.
PDB_path	PDB file path (default = NULL)
n_threads	number of threads (default = NULL)
gene_name_info	whether there is gene name information in the input or not (default = TRUE)
distance_cutoff	distance cutoff for setting edges (default = 5)
network_approach	network building approach; "all" (default) for using all atoms only or "ca" for using ca atoms only

Details

With an input data.frame which contains 'PDB_ID', 'Chain', 'Position', 'Reference Amino Acid', 'Mutated Amino Acid' and 'Gene_Name' (optional) information respectively, make a prediction about the impact of a mutation and classifies the mutation as 'Pathogenic' or 'Neutral'. Predictions can be done by using 7 angstrom cutoff - all atom approach or 5 angstrom cutoff - ca atom approach. Other cutoffs can be used for exploratory purposes.

Value

data.frame which contains prediction results

berkgurdamar/predatoR documentation built on Jan. 10, 2023, 10:51 p.m.