Jens Sauer
dbfcca9716
* visualize: Visualize asct per diagnosis per age Visualize asct per diagnosis per year Add basic histograms Remove unused factor levels from data after limiting
125 lines
3.6 KiB
R
125 lines
3.6 KiB
R
# secMalASCT utilities
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#
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# License: GPL version 3
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# Jens Mathis Sauer (c) 2020
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library(survival)
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library(survminer)
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library(tidyverse)
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#
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# Write plot to filename
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#
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# This will plot "fun" with arguments "..." as filetype "ftype" and
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# the output to "filename". Title and legends can be passed as list,
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# or NULL if not needed.
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# Default filesize is 3000x3000 px and 300 dpi resolution.
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#
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sma_plot_file <- function(fname, ftype, fun, width = 4000, height = 3000) {
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# Open file for writing
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ftype(filename = fname, width = width, height = height, res = 300)
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#
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# Write plot into variable, then printing it manually. This is
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# needed to save plots from package "survminer" at the moment.
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#
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# See: https://github.com/kassambara/survminer/issues/152
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#
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p <- fun()
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print(p)
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# hide "null device 1" in garbage
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garbage <- dev.off()
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}
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#
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# Load secMalASCT data
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#
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# This loads the secMalASCT data from a CSV file and adjusts some
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# columns to the correct type.
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#
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sma_load_data <- function(file) {
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sma <- as_tibble(read.csv(file, header = TRUE))
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# Type adjustments
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sma$follow_up_multi <- as.logical(sma$follow_up_multi)
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sma$nicotin_history <- as.logical(sma$nicotin_history)
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sma$relapse_treatment_asct <- as.logical(sma$relapse_treatment_asct)
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sma$relapse_treatment_chemotherapy <- as.logical(sma$relapse_treatment_chemotherapy)
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sma$relapse_treatment_radiotherapy <- as.logical(sma$relapse_treatment_radiotherapy)
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sma$relapse_treatment_surgery <- as.logical(sma$relapse_treatment_surgery)
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sma$pre_rt <- as.logical(sma$pre_rt)
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sma$pre_rt_type <- as.factor(sma$pre_rt_type)
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sma$post_rt <- as.logical(sma$post_rt)
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sma$post_rt_type <- as.factor(sma$post_rt_type)
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sma$pre_alkylating_agents <- as.logical(sma$pre_alkylating_agents)
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sma$pre_topoisomerase <- as.logical(sma$pre_topoisomerase)
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sma$pre_anthracyclines <- as.logical(sma$pre_anthracyclines)
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sma$peri_alkylating_agents <- as.logical(sma$peri_alkylating_agents)
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sma$peri_topoisomerase <- as.logical(sma$peri_topoisomerase)
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sma$peri_anthracyclines <- as.logical(sma$peri_anthracyclines)
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sma$post_alkylating_agents <- as.logical(sma$post_alkylating_agents)
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sma$post_topoisomerase <- as.logical(sma$post_topoisomerase)
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sma$post_anthracyclines <- as.logical(sma$post_anthracyclines)
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sma$maintenance_treatment <- as.logical(sma$maintenance_treatment)
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sma$maintenance_treatment_time <- as.integer(sma$maintenance_treatment_time)
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sma$maintenance_treatment_type <- as.factor(sma$maintenance_treatment_type)
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sma$thalidomid <- as.logical(sma$thalidomid)
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sma$bortezomib <- as.logical(sma$bortezomib)
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#
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# Limit to patients which are at least 16.0 years old at time
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# of transplantation.
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sma <- filter(sma, asct_age >= 16.0)
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# At this time only solid tumors are important
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sma <- filter(sma, diagnosis_type == "solid")
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# After filtering unused levels must be cleared from the data
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sma <- droplevels(sma)
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return(sma)
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}
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#
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# Global break.time.by value
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#
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sma_break.time.by = 5 * 365.25
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#
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# Initialize secMalASCT workspace
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#
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# This function can be called multiple times, the data will only
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# be loaded once. To manually reload data call:
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# > sma_init_force()
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#
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sma_init <- function() {
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if (exists("sma_initialized") == FALSE) {
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print("Initialize secMalASCT workspace")
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print("Loading data")
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#
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# Use superassignment operator '<<-' to make
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# secmal and sma_initialized with global scope.
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#
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secmal <<- sma_load_data("data/data.csv")
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sma_initialized <<- TRUE
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}
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}
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#
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# Force reinitialization of workspace
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#
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# Forcefully calls sma_init() again.
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#
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sma_init_force <- function() {
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print("Reloading secMalASCT data")
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remove(sma_initialized, pos = ".GlobalEnv")
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sma_init()
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}
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