R: Create a data frame of protein intensities

create_df {promor}

R Documentation

Create a data frame of protein intensities

Description

This function creates a data frame of protein intensities

Usage

create_df(
  prot_groups,
  exp_design,
  input_type = "MaxQuant",
  data_type = "LFQ",
  filter_na = TRUE,
  filter_prot = TRUE,
  uniq_pep = 2,
  tech_reps = FALSE,
  zero_na = TRUE,
  log_tr = TRUE,
  base = 2
)

Arguments

`prot_groups`	File path to a proteinGroups.txt file produced by MaxQuant or a standard input file containing a quantitative matrix where the proteins or protein groups are indicated by rows and the samples by columns.
`exp_design`	File path to a text file containing the experimental design.
`input_type`	Type of input file indicated by `prot_groups`. Available options are: "MaxQuant", if a proteinGroups.txt file is used, or "standard" if a standard input file is used. Default is "MaxQuant."
`data_type`	Type of sample protein intensity data columns to use from the proteinGroups.txt file. Some available options are "LFQ", "iBAQ", "Intensity". Default is "LFQ." User-defined prefixes in the proteinGroups.txt file are also allowed. The `data_type` argument is case-sensitive, and only applies when `input_type = "MaxQuant"`.
`filter_na`	Logical. If `TRUE`(default), filters out empty rows and columns from the data frame.
`filter_prot`	Logical. If `TRUE` (default), filters out reverse proteins, proteins only identified by site, potential contaminants, and proteins identified with less than the minimum number of unique peptides indicated by `uniq_pep`. Only applies when `input_type = "MaxQuant"`.
`uniq_pep`	Numerical. Proteins that are identified by this number or fewer number of unique peptides are filtered out (default is 2).Only applies when `input_type = "MaxQuant"`.
`tech_reps`	Logical. Indicate as `TRUE` if technical replicates are present in the data. Default is `FALSE`.
`zero_na`	Logical. If `TRUE` (default), zeros are considered missing values and replaced with NAs.
`log_tr`	Logical. If `TRUE` (default), intensity values are log transformed to the base indicated by `base`.
`base`	Numerical. Logarithm base. Default is 2.

Details

This function first reads in the proteinGroups.txt file produced by MaxQuant or a standard input file containing a quantitative matrix where the proteins or protein groups are indicated by rows and the samples by columns.
It then reads in the expDesign.txt file provided as exp_design and extracts relevant information from it to add to the data frame. an example of the expDesign.txt is provided here: https://raw.githubusercontent.com/caranathunge/promor_example_data/main/ed1.txt.
First, empty rows and columns are removed from the data frame.
Next, if a proteinGroups.txt file is used, it filters out reverse proteins, proteins that were only identified by site, and potential contaminants.Then it removes proteins identified with less than the number of unique peptides indicated by uniq_pep from the data frame.
Next, it extracts the intensity columns indicated by data type and the selected protein rows from the data frame.
Converts missing values (zeros) to NAs.
Finally, the function log transforms the intensity values.

Value

A raw_df object which is a data frame containing protein intensities. Proteins or protein groups are indicated by rows and samples by columns.

Author(s)

Chathurani Ranathunge

Examples



### Using a proteinGroups.txt file produced by MaxQuant as input.
## Generate a raw_df object with default settings. No technical replicates.
raw_df <- create_df(
  prot_groups = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/pg1.txt",
  exp_design = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/ed1.txt",
  input_type = "MaxQuant"
)

## Data containing technical replicates
raw_df <- create_df(
  prot_groups = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/pg2.txt",
  exp_design = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/ed2.txt",
  input_type = "MaxQuant",
  tech_reps = TRUE
)

## Alter the number of unique peptides needed to retain a protein
raw_df <- create_df(
  prot_groups = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/pg1.txt",
  exp_design = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/ed1.txt",
  input_type = "MaxQuant",
  uniq_pep = 1
)

## Use "iBAQ" values instead of "LFQ" values
raw_df <- create_df(
  prot_groups = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/pg1.txt",
  exp_design = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/ed1.txt",
  input_type = "MaxQuant",
  data_type = "iBAQ"
)

### Using a universal standard input file instead of MaxQuant output.
raw_df <- create_df(
  prot_groups = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/st.txt",
  exp_design = "https://raw.githubusercontent.com/caranathunge/promor_example_data/main/ed1.txt",
  input_type = "standard"
)

[Package promor version 0.2.1 Index]