PepMapViz (version 1.1.0)

calculate_PSM: 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
)

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.

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.

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
)