Preprocessing of raw data

Source: R/Main_functions.R

Preprocessing of raw data

preprocess_data(df, Column_gene_name = "Gene.names",
  Column_score = "Score", Column_ID = "Protein.IDs",
  Column_Npep = NULL, Column_intensity_pattern = "^Intensity.",
  bait_gene_name, condition = NULL, bckg_bait = bait_gene_name,
  bckg_ctrl = "WT", log = TRUE, filter_time = NULL,
  filter_bio = NULL, filter_tech = NULL, min_score = 0,
  filter_gene_name = TRUE, ...)

Arguments

df

Data.frame with protein intensities
Column_gene_name

Column with gene names
Column_score

Column with protein identification score
Column_ID

Column with protein IDs
Column_Npep

Column with number of theoretically observable peptides per protein
Column_intensity_pattern

Pattern (regular exrpression) used to identfy df's columns containing protein intensity values
bait_gene_name

The gene name of the bait
condition

data.frame with columns "column", bckg", "bio", "time" and "tech" indicating for each intensity column ("sample") its corresponding background ("bckg"), biologicla replicate ("bio), experimental condition ("tine) and technical replicate ("tech).
bckg_bait

Name of the bait background as found in condition$bckg (see below)
bckg_ctrl

Name of the control background as found in condition$bckg (see below)
log

logical, use geometric mean to average technical replicates
filter_time

vector of experimental conditions to exclude from analysis
filter_bio

vector of biological replicates to exclude from analysis
filter_tech

vector of technical replicates to exclude from analysis
min_score

threshold on identification score
filter_gene_name

logical, filter out proteins withy empty gene name
...

Additional parameters passed to function identify_conditions