| Title: | A Versatile Toolkit for Peptide Mapping, Visualization, and Comparative Exploration |
| Version: | 1.1.0 |
| 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. |
| License: | MIT + file LICENSE |
| Encoding: | UTF-8 |
| RoxygenNote: | 7.3.2 |
| Imports: | shiny, ggplot2, stringr, ggforce, ggh4x, ggnewscale, data.table, rlang, DT |
| Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0), mzID, MSnbase |
| Note: | The package 'MSnbase' is used for parsing and processing mzTab files. While its non-portability limits usage on some platforms, it is essential for enabling analysis and integration of mzTab data in 'PepMapViz'. However, if the input file is not in mzTab format, 'MSnbase' is not required, and the package can function without it. |
| Config/testthat/edition: | 3 |
| VignetteBuilder: | knitr |
| biocViews: | Immunogenicity, MassSpectrometry, Proteomics, Peptidomics, Software, Visualization |
| NeedsCompilation: | no |
| Packaged: | 2025-06-25 16:28:43 UTC; zhouz45 |
| Author: | Zhenru Zhou [aut, cre], Qui Phung [aut], Corey Bakalarski [aut] |
| Maintainer: | Zhenru Zhou <zhou.zhenru@gene.com> |
| Repository: | CRAN |
| Date/Publication: | 2025-06-25 17:10:06 UTC |
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 |
reps |
A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is |
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 |
reps |
A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is |
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
)
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 |
reps |
A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is |
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 |
reps |
A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is |
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
)
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 |
x_expand |
A numeric vector of length 2 specifying the expansion for the x-axis. Default is |
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 |
fill_gradient_options |
A list of options for |
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_end_column |
The name of the column in |
domain_type_column |
The name of the column in |
domain_border_color_column |
The name of the column in |
domain_fill_color_column |
The name of the column in |
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_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 |
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 |
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 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 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 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)
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"
)
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 |
reps |
A boolean parameter indicating whether the area/intensity should be divided by the number of replicates. Default is |
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 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 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 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')