Package 'PepMapViz'

Title: A Versatile Toolkit for Peptide Mapping, Visualization, and Comparative Exploration
Description: A versatile R visualization package that empowers researchers with comprehensive visualization tools for seamlessly mapping peptides to protein sequences, identifying distinct domains and regions of interest, accentuating mutations, and highlighting post-translational modifications, all while enabling comparisons across diverse experimental conditions. Potential applications of 'PepMapViz' include the visualization of cross-software mass spectrometry results at the peptide level for specific protein and domain details in a linearized format and post-translational modification coverage across different experimental conditions; unraveling insights into disease mechanisms. It also enables visualization of Major histocompatibility complex-presented peptide clusters in different antibody regions predicting immunogenicity in antibody drug development.
Authors: Zhenru Zhou [aut, cre], Qui Phung [aut], Corey Bakalarski [aut]
Maintainer: Zhenru Zhou <[email protected]>
License: MIT + file LICENSE
Version: 1.1.0
Built: 2026-05-21 06:41:40 UTC
Source: https://github.com/cran/PepMapViz

Help Index

Calculate Area/Intensity for the whole input sequence dataframe

Description

Calculate Area/Intensity for the whole input sequence dataframe

Usage

calculate_all_Area(
  whole_seq,
  matching_result,
  matching_columns,
  distinct_columns,
  area_column,
  with_PTM = FALSE,
  reps = FALSE
)

Arguments

whole_seq

A dataframe holding whole sequence information. 'Region_Sequence' column is required for the sequence information. Change the column name if it is different than 'Region_Sequence'.
matching_result

The dataframe that contains the matched results and PTM information.
matching_columns

Vector of column names that should match between each row of 'whole_seq' and the 'matching_result' dataframe.
distinct_columns

Vector of column names that should be used to calculate Area separately for each unique combination of these columns.
area_column

The name of the column in 'matching_result' that contains the area/intensity information.
with_PTM

A boolean parameter indicating whether PTM should be considered during calculation of Area. Default is FALSE.
reps

A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is FALSE.

Value

Returns data_with_area, a dataframe contains calculated Area for each record in 'whole_seq'.

Examples

whole_seq <- data.frame(
  Region_Sequence = c(
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD",
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD"
  ),
  Condition_1 = c(
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2"
  ),
  Condition_2 = c(
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2"
  ),
  Region_1 = c(
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL"
  ),
  Region_2 = c(
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2"
  )
)
matching_result <- data.frame(
  Sequence = c("AAA", "DDD", "DDD"),
  Condition_1 = c("Drug1", "Drug2", "Drug2"),
  Condition_2 = c("Donor1", "Donor2", "Donor2"),
  Region_1 = c("VH", "VL", "VL"),
  Region_2 = c("Arm_1", "Arm_2", "Arm_2"),
  start_position = c(4, 4, 4),
  end_position = c(6, 6, 6),
  PTM_position = c(NA, 2, 0),
  PTM_type = c(NA, "O", "C"),
  Area = c(100, 200, 200),
  reps = c(1, 2, 2)
)
matching_columns <- c("Condition_1", "Region_2")
area_column <- "Area"
data_with_area <- calculate_all_Area(
  whole_seq,
  matching_result,
  matching_columns,
  distinct_columns = c("Condition_2", "Region_1"),
  area_column,
  with_PTM = TRUE,
  reps = TRUE
)

Calculate Spectra Count (PSM) for the whole input sequence dataframe

Description

Calculate Spectra Count (PSM) for the whole input sequence dataframe

Usage

calculate_all_PSM(
  whole_seq,
  matching_result,
  matching_columns,
  distinct_columns,
  with_PTM = FALSE,
  reps = FALSE
)

Arguments

whole_seq

A dataframe holding whole sequence information. 'Region_Sequence' column is required for the sequence information. Change the column name if it is different than 'Region_Sequence'.
matching_result

The dataframe that contains the matched results and PTM information.
matching_columns

Vector of column names that should match between each row of 'whole_seq' and the 'matching_result' dataframe.
distinct_columns

Vector of column names that should be used to calculate PSM separately for each unique combination of these columns.
with_PTM

A boolean parameter indicating whether PTM should be considered during calculation of PSM. Default is FALSE.
reps

A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is FALSE.

Value

Returns data_with_psm, a dataframe contains calculated PSM for each record in 'whole_seq'.

Examples

whole_seq <- data.frame(
  Region_Sequence = c(
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD",
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD"
  ),
  Condition_1 = c(
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2"
  ),
  Condition_2 = c(
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2"
  ),
  Region_1 = c(
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL"
  ),
  Region_2 = c(
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2"
  )
)
matching_result <- data.frame(
  Sequence = c("AAA", "DDD", "DDD"),
  Condition_1 = c("Drug1", "Drug2", "Drug2"),
  Condition_2 = c("Donor1", "Donor2", "Donor2"),
  Region_1 = c("VH", "VL", "VL"),
  Region_2 = c("Arm_1", "Arm_2", "Arm_2"),
  start_position = c(4, 4, 4),
  end_position = c(6, 6, 6),
  PTM_position = c(NA, 2, 0),
  PTM_type = c(NA, "O", "C"),
  Area = c(100, 200, 200),
  reps = c(1, 2, 2)
)
matching_columns <- c("Condition_1", "Region_2")
data_with_psm <- calculate_all_PSM(
  whole_seq,
  matching_result,
  matching_columns,
  distinct_columns = c("Condition_2", "Region_1"),
  with_PTM = TRUE,
  reps = TRUE
)

Calculate Area/Intensity for one row of the input sequence dataframe

Description

Calculate Area/Intensity for one row of the input sequence dataframe

Usage

calculate_Area(
  row,
  matching_result,
  matching_columns,
  distinct_columns = NULL,
  area_column,
  with_PTM = FALSE,
  reps = FALSE
)

Arguments

row

A row of dataframe containing the sequence for the 'Character' column in region_data.
matching_result

The dataframe that contains the matched results and PTM information.
matching_columns

Vector of column names that should match between the 'row' and 'matching_result' dataframes.
distinct_columns

Vector of column names that should be used to calculate Area separately for each unique combination of these columns.
area_column

The name of the column in 'matching_result' that contains the area/intensity information.
with_PTM

A boolean parameter indicating whether PTM should be considered. If with_PTM = TRUE, the function will also add 'PTM' and 'PTM_type' to the result 'region_data' dataframe. Default is FALSE.
reps

A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is FALSE.

Value

This function returns the modified region_data dataframe that includes the "Area" column, and optionally "PTM" and "PTM_type" columns. If the 'filter_conditions' do not match, an empty dataframe will be returned early. An AttributeError is raised if 'PTM_position' and 'PTM_type' columns do not exist in the 'result' dataframe when 'with_PTM' is TRUE.

Examples

row <- data.frame(
 Region_Sequence = c("XYZAAA"),
 Condition_1 = c("Drug1"),
 Condition_2 = c("Donor1"),
 Region_1 = c("VH"),
 Region_2 = c("Arm_1")
)
matching_result <- data.frame(
  Sequence = c("AAA", "DDD", "DDD"),
  Condition_1 = c("Drug1", "Drug2", "Drug2"),
  Condition_2 = c("Donor1", "Donor2", "Donor2"),
  Region_1 = c("VH", "VL", "VL"),
  Region_2 = c("Arm_1", "Arm_2", "Arm_2"),
  start_position = c(4, 4, 4),
  end_position = c(6, 6, 6),
  PTM_position = c(NA, 2, 0),
  PTM_type = c(NA,"O","C"),
  Area = c(100, 200, 200),
  reps = c(1, 2, 2)
)
matching_columns <- c("Condition_1", "Region_2")
area_column <- "Area"
data_with_area <- calculate_Area(
  row,
  matching_result,
  matching_columns,
  distinct_columns = c("Condition_2", "Region_1"),
  area_column,
  with_PTM = TRUE,
  reps = TRUE
)

Calculate Spectra Count (PSM) for one row of the input sequence dataframe

Description

Calculate Spectra Count (PSM) for one row of the input sequence dataframe

Usage

calculate_PSM(
  row,
  matching_result,
  matching_columns,
  distinct_columns,
  with_PTM = FALSE,
  reps = FALSE
)

Arguments

row

A row of dataframe containing the sequence for the 'Character' column in region_data.
matching_result

The dataframe that contains the matched results and PTM information.
matching_columns

Vector of column names that should match between the 'row' and 'matching_result' dataframes.
distinct_columns

Vector of column names that should be used to calculate PSM separately for each unique combination of these columns.
with_PTM

A boolean parameter indicating whether PTM should be considered. If with_PTM = TRUE, the function will also add 'PTM' and 'PTM_type' to the result 'region_data' dataframe. Default is FALSE.
reps

A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is FALSE.

Value

This function returns the modified region_data dataframe that includes the "PSM" column, and optionally "PTM" and "PTM_type" columns. If the 'filter_conditions' do not match, an empty dataframe will be returned early. An AttributeError is raised if 'PTM_position' and 'PTM_type' columns do not exist in the 'result' dataframe when 'with_PTM' is TRUE.

Examples

row <- data.frame(
 Region_Sequence = c("XYZDDD"),
 Condition_1 = c("Drug2"),
 Region_1 = c("VL"),
 Region_2 = c("Arm_2")
)
matching_result <- data.frame(
  Sequence = c("AAA", "DDD", "DDD"),
  Condition_1 = c("Drug1", "Drug2", "Drug2"),
  Condition_2 = c("Donor1", "Donor2", "Donor2"),
  Region_1 = c("VH", "VL", "VL"),
  Region_2 = c("Arm_1", "Arm_2", "Arm_2"),
  start_position = c(4, 4, 4),
  end_position = c(6, 6, 6),
  PTM_position = c(NA, 2, 0),
  PTM_type = c(NA,"O","C"),
  Area = c(100, 200, 200),
  reps = c(1, 2, 2)
)
matching_columns <- c("Condition_1", "Region_2")
result <- calculate_PSM(
  row,
  matching_result,
  matching_columns,
  distinct_columns = c("Condition_2", "Region_1"),
  with_PTM = TRUE,
  reps = TRUE
)

Combine CSV and TXT Files from a Folder

Description

This function reads all CSV and TXT files from a specified folder and combines them into a single data.table.

Usage

combine_files_from_folder(folder_path)

Arguments

folder_path

The path to the folder containing the CSV or TSV files.

Value

A data.table containing the combined data from all files.

Examples

folder_path <- ""
combined_df <- combine_files_from_folder(folder_path)
print(combined_df)

Convert Peptide Sequence to Regex Pattern

Description

This function converts a peptide sequence into a regular expression pattern that accounts for ambiguous amino acids. Each amino acid is replaced by a character class that includes itself, 'X', and any specific ambiguities.

Usage

convert_to_regex_pattern(peptide)

Arguments

peptide

A character string representing the peptide sequence.

Value

A character string containing the regex pattern for matching.

Examples

# Convert a peptide sequence to a regex pattern
peptide <- "NDEQIL"
regex_pattern <- convert_to_regex_pattern(peptide)
print(regex_pattern) # Output: "[NBX][DBX][EZX][QZX][ILX][ILX]"

Create a peptide Plot

Description

This function generates a peptide plot using the provided data and allows for customization of the plot layout.

Usage

create_peptide_plot(
  data,
  y_axis_vars,
  x_axis_vars,
  y_expand = c(0.1, 0.15),
  x_expand = c(0.6, 0.6),
  theme_options = NULL,
  labs_options = NULL,
  color_fill_column,
  fill_gradient_options = list(),
  label_size = 3,
  add_domain = TRUE,
  domain = NULL,
  domain_start_column = "domain_start",
  domain_end_column = "domain_end",
  domain_type_column = "domain_type",
  domain_border_color_column = NULL,
  domain_fill_color_column = NULL,
  add_domain_label = TRUE,
  domain_label_size = 4,
  domain_label_y_column = NULL,
  domain_label_color = "black",
  PTM = FALSE,
  PTM_type_column = "PTM_type",
  PTM_color = NULL,
  add_label = TRUE,
  label_column = "Character",
  label_filter = NULL,
  label_y = 1.28,
  column_order = NULL
)

Arguments

data

A dataframe containing the PSM data or Area data got from peptide_cluster_quantification.
y_axis_vars

A list of variables for the donor and type facets.
x_axis_vars

A list of variables for the region facets.
y_expand

A numeric vector of length 2 specifying the expansion for the y-axis. Default is c(0.1, 0.15).
x_expand

A numeric vector of length 2 specifying the expansion for the x-axis. Default is c(0.6, 0.6).
theme_options

A list of additional theme options to customize the plot. Default is an empty list.
labs_options

A list of additional labs options to customize the plot labels. Default is an empty list.
color_fill_column

The name of the column in data_with_psm to be used for the fill aesthetic. Default is 'PSM'.
fill_gradient_options

A list of options for scale_fill_gradient. Default is an empty list.
label_size

The size of the labels in the plot. Default is 3.
add_domain

A logical value indicating whether to add domain like CDR (Complementarity-Determining Region) to the plot. Default is TRUE.
domain

A dataframe containing the domain data with columns including 'domain_start', 'domain_end', and 'domain_type'.
domain_start_column

The name of the column in domain containing the start position of the domain Default is 'domain_start'.
domain_end_column

The name of the column in domain containing the end position of the domain Default is 'domain_end'.
domain_type_column

The name of the column in domain containing the type of the domain Default is 'domain_type'.
domain_border_color_column

The name of the column in domain containing the border color of the domain Default is 'domain_color'.
domain_fill_color_column

The name of the column in domain containing the fill color of the domain Default is 'domain_fill_color'.
add_domain_label

Logical; whether to annotate the domain type as text above the domain rectangle. Default is TRUE.
domain_label_size

Numeric; text size for the domain label. Default is 4.
domain_label_y_column

The name of the column in domain containing y-axis position for the domain label. Default is 'domain_label_y'.
domain_label_color

Character; color for domain label text. Default is 'black'.
PTM

A logical value indicating whether to include PTM (Post-Translational Modification) data in the plot. Default is FALSE.
PTM_type_column

The name of the column in data_with_psm containing the type of the PTM. Default is 'PTM_type'.
PTM_color

A list of colors for the PTM types. Default is NULL.
add_label

A logical value indicating whether to add labels to the plot. Default is TRUE.
label_column

The name of the column in data_with_psm containing the labels to be added to the plot. Default is 'Character'.
label_filter

A list of column names and their values to filter the data for the labels. Default is NULL.
label_y

The position of y axis of the label.
column_order

A list of column names and their order for the plot. Default is NULL.

Value

This function returns a ggplot object representing the PSM plot.

Examples

data <- data.frame(
  Character = c("X", "Y", "Z", "A", "A", "A"),
  Position = 1:6,
  Condition_1 = rep("Drug1", 6),
  Region_2 = rep("Arm_1", 6),
  Area = c(0.000000, 0.000000, 0.000000, 6.643856, 6.643856, 6.643856),
  Condition_2 = rep("Donor1", 6),
  Region_1 = rep("VH", 6),
  PTM = c(FALSE, TRUE, FALSE, FALSE, FALSE, FALSE),
  PTM_type = c(NA, "O", NA, NA, NA, NA)
)
domain <- data.frame(
  domain_type = c("CDR H1", "CDR H2", "CDR H3"),
  Region_1 = c("VH", "VH", "VH"),
  Region_2 = c("Arm_1", "Arm_1", "Arm_1"),
  Condition_1 = c("Drug1", "Drug1", "Drug1"),
  domain_start = c(1, 3, 5),
  domain_end = c(2, 4, 6),
  domain_color = c("#F8766D", "#B79F00", "#00BA38"),
  domain_fill_color = c("#F8766D", "#B79F00", "#00BA38"),
  domain_label_y = c(1.35, 1.35, 1.35)
)
x_axis_vars <- c("Region_2", "Region_1")
y_axis_vars <- c("Condition_2")
PTM_color <- c(
  "Ox" = "red",
  "Deamid" = "cyan",
  "Cam" = "blue",
  "Acetyl" = "magenta"
)
p <- create_peptide_plot(
  data,
  y_axis_vars,
  x_axis_vars,
  y_expand = c(0.2, 0.2),
  x_expand = c(0.5, 0.5),
  theme_options = list(),
  labs_options = list(title = "Area Plot", x = "Position", fill = "Area"),
  color_fill_column = 'Area',
  fill_gradient_options = list(),
  label_size = 5,
  add_domain = TRUE,
  domain = domain,
  domain_start_column = "domain_start",
  domain_end_column = "domain_end",
  domain_type_column = "domain_type",
  domain_border_color_column = "domain_color",
  domain_fill_color_column = "domain_fill_color",
  add_domain_label = TRUE,
  domain_label_size = 4,
  domain_label_y_column = "domain_label_y",
  domain_label_color = "black",
  PTM = FALSE,
  PTM_type_column = "PTM_type",
  PTM_color = PTM_color,
  add_label = TRUE,
  label_column = "Character",
  label_filter = NULL,
  label_y = 1,
  column_order = list(Region_1 = 'VH')
)
print(p)

Match peptide sequence with provided sequence and calculate positions

Description

This function matches peptide sequences from the 'peptide_data' data frame to corresponding provided sequences in the 'whole_seq' data frame. It calculates the start and end positions of the matched sequences and returns a data frame with information about the matching positions.

Usage

match_and_calculate_positions(
  peptide_data,
  column,
  whole_seq,
  match_columns,
  sequence_length = NULL,
  column_keep = NULL
)

Arguments

peptide_data

A data frame containing peptide sequence information to match.
column

The name of the column in peptide_data containing the peptide sequences to be matched.
whole_seq

A data frame containing details about antibody sequence information including the domain and region information. 'Region_Sequence' column is required for the sequence information. Change the column name if it is different than 'Region_Sequence'.
match_columns

A character vector of column names that must exist in both peptide_data and whole_seq. When searching for peptide sequence matches, the function will only consider rows in whole_seq where the values in all columns specified here exactly match the corresponding values in the current row of peptide_data.
sequence_length

(Optional) The sequence length range of peptide that we want to keep in the result. (e.g. c(1, 5) will include peptide sequence length from 1 to 5.)
column_keep

(Optional) The name of the columns in peptide_data to keep in result data frame.

Value

A data frame with columns from 'peptide_data' and 'whole_seq' indicating the matched positions and related information.

Examples

peptide_data <- data.frame(
  Sequence = c("AILNK", "BXLMR", "JJNXX", "DDEEF"),
  Condition_1 = c("Drug1", "Drug1", "Drug2", "Drug2"),
  Condition_2 = c("Donor1", "Donor2", "Donor1", "Donor2"),
  Region_1 = c("VH", "VL", "VH", "VL"),
  Region_2 = c("Arm_1", "Arm_2", "Arm_1", "Arm_2"),
  Area = c(100, 2, 4, NA)
)
whole_seq <- data.frame(
  Region_Sequence = c(
    "XYZAILNKPQR",
    "ABCBXLMRDEF",
    "GHIJJNXXKLM",
    "NOPDDEEFQRS",
    "AILXKPQR",
    "BNJLMRDEF",
    "ILNXXKLM",
    "DDEEXQRS",
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD"
  ),
  Condition_1 = c(
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2"
  ),
  Condition_2 = c(
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2"
  ),
  Region_1 = c(
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL"
  ),
  Region_2 = c(
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2"
  )
)
match_columns <- c("Condition_1", "Condition_2", "Region_1")
column_keep <- c("Region_2")
sequence_length <- c(1, 5)
column <- "Sequence"
matching_result <- match_and_calculate_positions(peptide_data,
                                                 column,
                                                 whole_seq,
                                                 match_columns,
                                                 sequence_length,
                                                 column_keep)

Obtain post translational modification(PTM) information from Peptide data based on the specified data type

Description

This function takes outputs from multiple platform, a data frame with column containing modified peptide sequence with the detailed post translational modification(PTM) information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information. Due to the flexibility of outputs from multiple platform, the PTM mass to type table needs to be provided if convertion to PTM_type is needed. The result includes 'Peptide', 'PTM_position', 'PTM_type' and 'PTM_mass' columns.The function chooses the appropriate converting method based on the specified data type ('PEAKS', 'Spectronaut', 'MSFragger', 'Comet', 'DIANN', 'Skyline', 'Maxquant', 'mzIdenML' or 'mzTab'), allowing you to convert the data into a consistent format for further analysis.

Usage

obtain_mod(
  data,
  mod_column,
  type,
  seq_column = NULL,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data frame with the peptide sequences.
mod_column

The name of the column containing the modified peptide sequences.
type

A character string specifying the data type (e.g. 'Skyline' or 'Maxquant').
seq_column

(Optional) The name of the column containing peptide sequences for MSFragger, mzid and mzTab. This parameter is required for the "MSFragger", "mzIdenML" and "mzTab" type and can be omitted for other types.
PTM_table

A data frame with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information.

Value

A data.table with 'PTM_position', 'PTM_type', 'PTM_mass', 'reps', and other columns.

Examples

library(data.table)
data_skyline <- data.table(
  'Peptide Modified Sequence' = c(
    "AGLC[+57]QTFVYGGC[+57]R",
    "AAAASAAEAGIATTGTEDSDDALLK",
    "IVGGWEC[+57]EK"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(
  PTM_mass = c(57.02, -0.98, 15.9949),
  PTM_type = c("Cam", "Amid", "Ox")
)
converted_data_skyline <- obtain_mod(
  data_skyline,
  'Peptide Modified Sequence',
  'Skyline',
  seq_column = NULL,
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

data_maxquant <- data.table(
  'Modified sequence' = c(
    "_(ac)AAAAELRLLEK_",
    "_EAAENSLVAYK_",
    "_AADTIGYPVM(ox)IRSAYALGGLGSGICPNK_"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(
  PTM_mass = c('Phospho (STY)', 'Oxidation (M)'),
  PTM_type = c("Phos", "Ox")
)
converted_data_maxquant <- obtain_mod(
  data_maxquant,
  'Modified sequence',
  'Maxquant',
  seq_column = NULL,
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by Comet

Description

This function takes Comet output containing a column with modified peptide sequences including PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_Comet(
  data,
  mod_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing PTM information.
mod_column

The name of the column containing the modified peptide sequences.
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  modified_peptide = c(
    "AAM[15.9949]Q[-0.98]RGSLYQCDYSTGSC[57.02]EPIR",
    "K.AAQQTGKLVHANFGT.K",
    "K.[-0.98]AATVTGKLVHANFGT.K"
  ),
  plain_peptide = c(
    "AAMQRGSLYQCDYSTGSCEPIR",
    "AAQQTGKLVHANFGT",
    "AATVTGKLVHANFGT"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(
  PTM_mass = c(57.02, -0.98, 15.9949),
  PTM_type = c("Cam", "Amid", "Ox")
)
mod_column <- 'modified_peptide'
PTM_mass_column <- "PTM_mass"
converted_data <- obtain_mod_Comet(data, mod_column, PTM_table,
PTM_annotation = TRUE, PTM_mass_column)

Obtain modification information from Peptide data generated by DIA-NN

Description

This function takes DIA-NN output containing a column with modified peptide sequences including PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_DIANN(
  data,
  mod_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A dataframe with 'Stripped.Sequence' column and 'Modified.Sequence' column containing modified peptide sequences.
mod_column

The name of the column containing the modified peptide sequences.
PTM_table

A dataframe with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A dataframe with 'Peptide', 'PTM_position', and 'PTM_type' columns.

Examples

library(data.table)
data <- data.table(
  Modified.Sequence = c(
    "AAAAGPGAALS(UniMod:21)PRPC(UniMod:4)DSDPATPGAQSPK",
    "AAAASAAEAGIATTGTEDSDDALLK",
    "AAAAALSGSPPQTEKPT(UniMod:21)HYR"
  ),
  Stripped.Sequence = c(
    "AAAAGPGAALSPRPCDSDPATPGAQSPK",
    "AAAASAAEAGIATTGTEDSDDALLK",
    "AAAAALSGSPPQTEKPTHYR"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(PTM_mass = c('UniMod:21', 'UniMod:4'),
                        PTM_type = c("Phos", "Cam"))
converted_data <- obtain_mod_DIANN(
  data,
  'Modified.Sequence',
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by Maxquant

Description

This function takes Maxquant output containing a column with modified peptide sequences including PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_Maxquant(
  data,
  mod_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing modified peptide sequences.
mod_column

The name of the column containing the modified peptide sequences.
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  'Modified sequence' = c(
    "_GLGPSPAGDGPS(Phospho (STY))GSGK_",
    "_HSSYPAGTEDDEGM(Oxidation (M))GEEPSPFR_",
    "_HSSYPAGTEDDEGM(Oxidation (M))GEEPS(Phospho (STY))PFR_"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(
  PTM_mass = c('Phospho (STY)', 'Oxidation (M)'),
  PTM_type = c("Phos", "Ox")
)
converted_data <- obtain_mod_Maxquant(
  data,
  'Modified sequence',
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by MSFragger

Description

This function takes MSFragger output containing a 'Assigned Modifications' column with PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_MSFragger(
  data,
  mod_column,
  seq_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing stripped sequence and a column containing PTM information.
mod_column

The name of the column containing the modified peptide sequences.
seq_column

The name of the column containing peptide sequences for MSFragger.
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  Peptide = c("DDREDMLVYQAK", "EAAENSLVAYK", "IEAELQDICNDVLELLDK"),
  `Assigned Modifications` = c("C-term(15.9949), 6M(-0.98)", "", "N-term(42.0106)"),
  Condition1 = c("A", "B", "B"),
  Condition2 = c("C", "C", "D")
)
PTM_table <- data.table(
  PTM_mass = c(42.0106, -0.98, 15.9949),
  PTM_type = c("Acet", "Amid", "Ox")
)
mod_column <- "Assigned Modifications"
seq_column <- "Peptide"
converted_data <- obtain_mod_MSFragger(
  data,
  mod_column,
  seq_column,
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by mzIdenML

Description

This function takes mzIdenML output containing a 'modification' column with PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_mzIdenML(
  data,
  mod_column,
  seq_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing stripped sequence and a column containing PTM information.
mod_column

The name of the column containing the modified peptide sequences.
seq_column

The name of the column containing peptide sequences for mzIdenML.
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  pepseq = c("DDREDMLVYQAK", "EAAENSLVAYK", "IEAELQDICNDVLELLDK"),
  modification = c("-0.984016 (10), 15.994915 (13)", NA, "15.994915 (12)"),
  Condition1 = c("A", "B", "B"),
  Condition2 = c("C", "C", "D")
)
PTM_table <- data.table(
  PTM_mass = c(-0.984016, 15.994915),
  PTM_type = c("Amid", "Ox")
)
mod_column <- "modification"
seq_column <- "pepseq"
converted_data <- obtain_mod_mzIdenML(
  data,
  mod_column,
  seq_column,
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by mzTab

Description

This function takes mzTab output containing a 'modifications' column with PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_mzTab(
  data,
  mod_column,
  seq_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing stripped sequence and a column containing PTM information.
mod_column

The name of the column containing the modified peptide sequences.
seq_column

The name of the column containing peptide sequences for mzTab
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  sequence = c("DDREDMLVYQAK", "EAAENSLVAYK", "IEAELQDICNDVLELLDK"),
  modifications = c("4-UNIMOD:7,10-UNIMOD:35", NA, "8-UNIMOD:7"),
  Condition1 = c("A", "B", "B"),
  Condition2 = c("C", "C", "D")
)
PTM_table <- data.table(
  PTM_mass = c("UNIMOD:7", "UNIMOD:35"),
  PTM_type = c("Amid", "Ox")
)
mod_column <- "modifications"
seq_column <- "sequence"
converted_data <- obtain_mod_mzTab(
  data,
  mod_column,
  seq_column,
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by PEAKS

Description

This function takes PEAKS output containing a column with modified peptide sequences including PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_PEAKS(
  data,
  mod_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A dataframe with a column containing modified peptide sequences.
mod_column

The name of the column containing the modified peptide sequences.
PTM_table

A dataframe with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'PTM_mass', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  Peptide = c(
    "AAN(+42)Q(-0.98)RGSLYQCDYSTGSC(+57.02)EPIR",
    "K.AAQQTGKLVHANFGT.K",
    "K.(-0.98)AATVTGKLVHANFGT.K"
  ),
  Sequence = c(
    "AANQRGSLYQCDYSTGSCEPIR",
    "AAQQTGKLVHANFGT",
    "AATVTGKLVHANFGT"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(PTM_mass = c(42, -0.98, 57.02),
                        PTM_type = c("Acet", "Amid", "Cam"))
mod_column <- "Peptide"
PTM_mass_column <- "PTM_mass"
converted_data <- obtain_mod_PEAKS(data, mod_column, PTM_table,
PTM_annotation = TRUE, PTM_mass_column)

Obtain modification information from Peptide data generated by Skyline

Description

This function takes Skyline output containing a column with modified peptide sequences including PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_Skyline(
  data,
  mod_column,
  PTM_table,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing PTM information.
mod_column

The name of the column containing the modified peptide sequences.
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  'Peptide Modified Sequence' = c(
    "AAM[15.9949]Q[-0.98]RGSLYQCDYSTGSC[57.02]EPIR",
    "AAQQTGKLVHANFGT",
    "[-0.98]AATVTGKLVHANFGT"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(
  PTM_mass = c(57.02, -0.98, 15.9949),
  PTM_type = c("Cam", "Amid", "Ox")
)
converted_data <- obtain_mod_Skyline(
  data,
  'Peptide Modified Sequence',
  PTM_table,
  PTM_annotation = TRUE,
  PTM_mass_column = "PTM_mass"
)

Obtain modification information from Peptide data generated by Spectronaut

Description

This function takes Spectronaut output containing a column with modified peptide sequences including PTM information and converts it into a new dataframe with the desired format of peptide sequences and associated PTM information.

Usage

obtain_mod_Spectronaut(
  data,
  mod_column,
  PTM_table = NULL,
  PTM_annotation = FALSE,
  PTM_mass_column
)

Arguments

data

A data.table with a column containing modified peptide sequences.
mod_column

The name of the column containing the modified peptide sequences.
PTM_table

A data.table with columns 'PTM_mass' and 'PTM_type' containing PTM annotation information.
PTM_annotation

A logical value indicating whether to include PTM annotation information in the result.
PTM_mass_column

The name of the column containing the PTM mass information

Value

A data.table with 'PTM_position', 'PTM_type', 'reps', and other columns.

Examples

library(data.table)
data <- data.table(
  EG.ModifiedPeptide = c(
    "_[Acetyl (Protein N-term)]M[Oxidation (M)]DDREDLVYQAK_",
    "_EAAENSLVAYK_",
    "_IEAELQDIC[Carbamidomethyl (C)]NDVLELLDK_"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(
  PTM_mass = c(
    'Acetyl (Protein N-term)',
    'Oxidation (M)',
    'Carbamidomethyl (C)'
  ),
  PTM_type = c("Acet", "Ox", "Cam")
)
converted_data <- obtain_mod_Spectronaut(data, 'EG.ModifiedPeptide',
                                         PTM_table, PTM_annotation = TRUE,
                                         PTM_mass_column = "PTM_mass")
data <- data.table(
  EG.IntPIMID = c(
    "_[+42]M[-0.98]DDREDLVYQAK_",
    "_EAAENSLVAYK_",
    "_IEAELQDIC[+57]NDVLELLDK_"
  ),
  Condition = c("A", "B", "B")
)
PTM_table <- data.table(PTM_mass = c(42, -0.98, 57),
                        PTM_type = c("Acet", "Amid", "Cam"))
PTM_mass_column <- "PTM_mass"
converted_data <- obtain_mod_Spectronaut(data,
                                         'EG.IntPIMID',
                                         PTM_table,
                                         PTM_annotation = TRUE,
                                         PTM_mass_column)

Peptide Quantification

Description

Peptide Quantification

Usage

peptide_quantification(
  whole_seq,
  matching_result,
  matching_columns,
  distinct_columns,
  quantify_method,
  area_column = NULL,
  with_PTM = FALSE,
  reps = FALSE
)

Arguments

whole_seq

A dataframe holding whole sequence information. 'Region_Sequence' column is required for the sequence information. Change the column name if it is different than 'Region_Sequence'.
matching_result

The dataframe that contains the matched results and PTM information.
matching_columns

Vector of column names that should match between each row of 'whole_seq' and the 'matching_result' dataframe.
distinct_columns

Vector of column names that should be used to calculate PSM or Area separately for each unique combination of these columns.
quantify_method

A string indicating the quantification method. It can be either "PSM" or "Area".
area_column

The name of the column in 'matching_result' that contains the area/intensity information. Required if quantify_method is "Area".
with_PTM

A boolean parameter indicating whether PTM should be considered during calculation. Default is FALSE.
reps

A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is FALSE.

Value

Returns a dataframe containing the calculated PSM or Area for each record in 'whole_seq'.

Examples

whole_seq <- data.frame(
  Region_Sequence = c(
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD",
    "XYZAAA",
    "XYZCCC",
    "XYZBBB",
    "XYZDDD",
    "XYZAAB",
    "XYZCCD",
    "XYZBBB",
    "XYZDDD"
  ),
  Condition_1 = c(
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2",
    "Drug1",
    "Drug1",
    "Drug2",
    "Drug2"
  ),
  Condition_2 = c(
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor1",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2",
    "Donor2"
  ),
  Region_1 = c(
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL",
    "VH",
    "VL"
  ),
  Region_2 = c(
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_1",
    "Arm_2",
    "Arm_2",
    "Arm_2",
    "Arm_2"
  )
)
matching_result <- data.frame(
  Sequence = c("AAA", "DDD", "DDD"),
  Condition_1 = c("Drug1", "Drug2", "Drug2"),
  Condition_2 = c("Donor1", "Donor2", "Donor2"),
  Region_1 = c("VH", "VL", "VL"),
  Region_2 = c("Arm_1", "Arm_2", "Arm_2"),
  start_position = c(4, 4, 4),
  end_position = c(6, 6, 6),
  PTM_position = c(NA, 2, 0),
  PTM_type = c(NA, "O", "C"),
  Area = c(100, 200, 200),
  reps = c(1, 2, 2)
)
matching_columns <- c("Condition_1", "Region_2")
area_column <- "Area"
data_with_quantification <- peptide_quantification(
  whole_seq,
  matching_result,
  matching_columns,
  distinct_columns = c("Condition_2", "Region_1"),
  quantify_method = "Area",
  area_column = area_column,
  with_PTM = TRUE,
  reps = TRUE
)

Launch PepMapViz Shiny Application

Description

This function launches a Shiny application that provides an interactive interface for the PepMapViz package functionality.

Usage

run_pepmap_app(...)

Arguments

...

Additional arguments to pass to shiny::runApp()

Value

The Shiny application object

Examples

## Not run: 
run_pepmap_app()

## End(Not run)

Strip peptide sequences based on the specified data type

Description

This function takes outputs from multiple platform, a data frame with a column containing peptide sequences to be stripped, and a column where the stripped sequences will be stored. The function chooses the appropriate stripping method based on the specified data type ('PEAKS', 'Spectronaut', 'MSFragger', 'Comet', 'DIANN', 'Skyline' or 'Maxquant').

Usage

strip_sequence(data, column, convert_column, type)

Arguments

data

A data frame with the peptide sequences.
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.
type

A character string specifying the data type (e.g. 'Skyline' or 'Maxquant').

Value

A data frame with the specified column containing stripped sequences.

Examples

library(data.table)
data_skyline <- data.table(
  'Peptide Modified Sequence' = c(
    "AGLC[+57]QTFVYGGC[+57]R",
    "AAAASAAEAGIATTGTEDSDDALLK",
    "IVGGWEC[+57]EK"
  ),
  Condition = c("A", "B", "B")
)
data_maxquant <- data.table(
  'Modified sequence' = c(
    "_(ac)AAAAELRLLEK_",
    "_EAAENSLVAYK_",
    "_AADTIGYPVM(ox)IRSAYALGGLGSGICPNK_"
  ),
  Condition = c("A", "B", "B")
)

converted_data_skyline <- strip_sequence(data_skyline,
                                         'Peptide Modified Sequence',
                                         'Sequence',
                                         "Skyline")
converted_data_maxquant <- strip_sequence(data_maxquant, 'Modified sequence',
                                          'Sequence', "Maxquant")

Strip sequence from Comet outputs

Description

This function takes Comet output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_Comet(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  modified_peptide = c(
    "AAM[15.9949]Q[-0.98]RGSLYQCDYSTGSC[57.02]EPIR",
    "K.AAQQTGKLVHANFGT.K",
    "K.[0.98]AATVTGKLVHANFGT.K"
  ),
  Condition = c("A", "B", "B")
)
column <- 'modified_peptide'
convert_column <- 'Sequence'
converted_data <- strip_sequence_Comet(data, column, convert_column)

Strip sequence from DIANN outputs

Description

This function takes DIANN output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_DIANN(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  Modified.Sequence = c(
    "AAAAGPGAALS(UniMod:21)PRPC(UniMod:4)DSDPATPGAQSPK",
    "AAAASAAEAGIATTGTEDSDDALLK",
    "AAAAALSGSPPQTEKPT(UniMod:21)HYR"
  ),
  Condition = c("A", "B", "B")
)
column <- 'Modified.Sequence'
convert_column <- 'Sequence'
converted_data <- strip_sequence_DIANN(data, column, convert_column)

Strip sequence from Maxquant outputs

Description

This function takes Maxquant output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_Maxquant(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  'Modified sequence' = c(
    "_(ac)AA(ox)AAELRLLEK_",
    "_EAAENSLVAYK_",
    "_AADTIGYPVM(ox)IRSAYALGGLGSGICPNK_"
  ),
  Condition = c("A", "B", "B")
)
column <- 'Modified sequence'
convert_column <- 'Sequence'
converted_data <- strip_sequence_Maxquant(data, column, convert_column)

Strip sequence from MSFragger outputs

Description

This function takes MSFragger output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_MSFragger(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  'Modified Peptide' = c(
    "AAM[15.9949]Q[-0.98]RGSLYQCDYSTGSC[57.02]EPIR",
    "K.AAQQTGKLVHANFGT.K",
    "K.[0.98]AATVTGKLVHANFGT.K"
  ),
  Condition = c("A", "B", "B")
)
column <- 'Modified Peptide'
convert_column <- 'Sequence'
converted_data <- strip_sequence_MSFragger(data, 'Modified Peptide', 'Sequence')

Strip sequence from PEAKS outputs

Description

This function takes PEAKS output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_PEAKS(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  Peptide = c(
    "AAN(+0.98)Q(-0.98)RGSLYQCDYSTGSC(+57.02)EPIR",
    "K.AAQQTGKLVHANFGT.K",
    "K.(+0.98)AATVTGKLVHANFGT.K"
  ),
  Condition = c("A", "B", "B")
)
column <- "Peptide"
convert_column <- "Sequence"
converted_data <- strip_sequence_PEAKS(data, column, convert_column)

Strip sequence from Skyline outputs

Description

This function takes Skyline output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_Skyline(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  'Peptide Modified Sequence' = c(
    "AGLC[+57]QTFVYGGC[+57]R",
    "AAAASAAEAGIATTGTEDSDDALLK",
    "IVGGWEC[+57]EK"
  ),
  Condition = c("A", "B", "B")
)
column <- 'Peptide Modified Sequence'
convert_column <- 'Sequence'
converted_data <- strip_sequence_Skyline(data, column, convert_column)

Strip sequence from Spectronaut outputs

Description

This function takes Spectronaut output containing a column with peptide sequences to be stripped and converts it into a new dataframe with the stripped sequence

Usage

strip_sequence_Spectronaut(data, column, convert_column)

Arguments

data

A dataframe with a column containing peptide sequences to be stripped
column

The name of the column containing the peptide sequences to be stripped.
convert_column

The name of the column where the stripped sequences will be stored.

Value

A dataframe with a column containing stripped sequence

Examples

library(data.table)
data <- data.table(
  EG.IntPIMID = c(
    "_[+42]M[-16]DDREDLVYQAK_",
    "_EAAENSLVAYK_",
    "_IEAELQDIC[+57]NDVLELLDK_"
  ),
  Condition = c("A", "B", "B")
)
converted_data <- strip_sequence_Spectronaut(data, 'EG.IntPIMID', 'Sequence')