calculate_PSM: Calculate Spectra Count (PSM) for one row of the input...

In PepMapViz: A Versatile Toolkit for Peptide Mapping, Visualization, and Comparative Exploration

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
)

PepMapViz documentation built on April 3, 2025, 6:29 p.m.