calculate_all_PSM: Calculate Spectra Count (PSM) for the whole input sequence...

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

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
)

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