From 43f6de2279bd2746546a252e144b5b7376dda339 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Wed, 2 Aug 2023 11:25:20 +0200 Subject: [PATCH 01/25] Update test-fit_powerlaw_tail_optim.R --- tests/testthat/test-fit_powerlaw_tail_optim.R | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/tests/testthat/test-fit_powerlaw_tail_optim.R b/tests/testthat/test-fit_powerlaw_tail_optim.R index 781fcf5d..a28082ab 100644 --- a/tests/testthat/test-fit_powerlaw_tail_optim.R +++ b/tests/testthat/test-fit_powerlaw_tail_optim.R @@ -4,6 +4,16 @@ set_cevomod_verbosity(0) object <- tcga_brca_test |> intervalize_mutation_frequencies() +name <- "powerlaw_optim" +bootstraps <- NULL +allowed_zero_bins <- 2 +y_treshold <- 1 +y_threshold_pct <- 0.01 +av_filter <- c(1/3, 1/3, 1/3) +peak_detection_upper_limit <- 0.3 +reward_upper_limit <- 0.4 +control <- list(maxit = 1000, ndeps = c(0.1, 0.01)) + test_that("fit_powerlaw_tail_optim models have non-negative objective fun value", { object <- fit_powerlaw_tail_optim(object) From 0eee818183b2468fbf7287c6fa32b3cdcc73bac8 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Wed, 2 Aug 2023 11:29:17 +0200 Subject: [PATCH 02/25] intervalize_mutation_frequencies() as method --- NAMESPACE | 2 ++ R/prepare_snvs.R | 36 ++++++++++++++++++++----- man/intervalize_mutation_frequencies.Rd | 17 ++++++++++-- 3 files changed, 46 insertions(+), 9 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 87bc5360..ce00c74e 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -42,6 +42,8 @@ S3method(get_selection_coefficients,cevodata) S3method(get_selection_coefficients,tbl_df) S3method(identify_non_neutral_tail_mutations,cevodata) S3method(identify_non_neutral_tail_mutations,singlepatient_cevodata) +S3method(intervalize_mutation_frequencies,cevo_snvs) +S3method(intervalize_mutation_frequencies,cevodata) S3method(merge,cevodata) S3method(plot,cevo_ITH_tbl) S3method(plot,cevo_MC_solutions_eval) diff --git a/R/prepare_snvs.R b/R/prepare_snvs.R index 690c93be..1a9d5d43 100644 --- a/R/prepare_snvs.R +++ b/R/prepare_snvs.R @@ -105,19 +105,41 @@ dentro_2015_correction <- function(tbl) { #' #' @return object #' @export -intervalize_mutation_frequencies <- function(object, - which_snvs = default_SNVs(object), - column = get_frequency_measure_name(object, which_snvs), - bins = NULL, - verbose = get_cevomod_verbosity()) { - msg("Calculating f intervals, using ", column, " column", verbose = verbose) +intervalize_mutation_frequencies <- function(object, ...) { + UseMethod("intervalize_mutation_frequencies") +} + + + +#' @rdname intervalize_mutation_frequencies +#' @export +intervalize_mutation_frequencies.cevodata <- function(object, + which_snvs = default_SNVs(object), + column = get_frequency_measure_name(object, which_snvs), + bins = NULL, + verbose = get_cevomod_verbosity(), + ...) { snvs <- SNVs(object, which_snvs) |> - cut_f_intervals(bins = bins, column = column) + intervalize_mutation_frequencies(column, bins, verbose) object |> add_SNV_data(snvs, name = which_snvs) } +#' @rdname intervalize_mutation_frequencies +#' @export +intervalize_mutation_frequencies.cevo_snvs <- function(object, + column = get_frequency_measure_name(object), + bins = NULL, + verbose = get_cevomod_verbosity(), + ...) { + msg("Calculating f intervals, using ", column, " column", verbose = verbose) + object |> + cut_f_intervals(bins = bins, column = column) |> + as_cevo_snvs() +} + + #' Decide which mutation frequency measure to use #' #' Used during the intervalization of mutation frequencies. Uses CCF/2 if found diff --git a/man/intervalize_mutation_frequencies.Rd b/man/intervalize_mutation_frequencies.Rd index 72dc31e9..73c981b5 100644 --- a/man/intervalize_mutation_frequencies.Rd +++ b/man/intervalize_mutation_frequencies.Rd @@ -2,14 +2,27 @@ % Please edit documentation in R/prepare_snvs.R \name{intervalize_mutation_frequencies} \alias{intervalize_mutation_frequencies} +\alias{intervalize_mutation_frequencies.cevodata} +\alias{intervalize_mutation_frequencies.cevo_snvs} \title{Intervalize the mutation frequencies} \usage{ -intervalize_mutation_frequencies( +intervalize_mutation_frequencies(object, ...) + +\method{intervalize_mutation_frequencies}{cevodata}( object, which_snvs = default_SNVs(object), column = get_frequency_measure_name(object, which_snvs), bins = NULL, - verbose = get_cevomod_verbosity() + verbose = get_cevomod_verbosity(), + ... +) + +\method{intervalize_mutation_frequencies}{cevo_snvs}( + object, + column = get_frequency_measure_name(object), + bins = NULL, + verbose = get_cevomod_verbosity(), + ... ) } \arguments{ From 9464ce8c55a8bd3ef4c5c43346a9a1de6c50f506 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 09:51:53 +0200 Subject: [PATCH 03/25] bootstrapping v1 --- DESCRIPTION | 3 +- NAMESPACE | 1 + R/fit_powerlaw_tail_optim.R | 123 ++++++++++++++++-- man/powerlaw_optim.Rd | 24 +++- tests/testthat/test-fit_powerlaw_tail_optim.R | 1 + 5 files changed, 139 insertions(+), 13 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index afbe08cc..19ecffb8 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -30,7 +30,8 @@ Suggests: testthat (>= 3.0.0), tidyverse, vdiffr, - readthis + readthis, + rsample Config/testthat/edition: 3 VignetteBuilder: knitr Imports: diff --git a/NAMESPACE b/NAMESPACE index ce00c74e..508b09fb 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -26,6 +26,7 @@ S3method(evaluate_MC_runs,matrix) S3method(filter,cevodata) S3method(fit_mobster,cevodata) S3method(fit_powerlaw_tail_fixed,cevodata) +S3method(fit_powerlaw_tail_optim,cevo_SFS_tbl) S3method(fit_powerlaw_tail_optim,cevodata) S3method(get_CNVs_var_names,cevodata) S3method(get_frequency_measure_name,cevo_snvs) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index 89dba0fb..93dd4528 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -1,5 +1,5 @@ -#' Fitting Tung Durrett models +#' Fitting power-law tails with aptimum exponent value #' #' `fit_powerlaw_tail_optim()` uses `stats::optim` to find optimal A and alpha #' whch maximizes SFS area under the powerlaw curve (*sampled* region of SFS and @@ -35,12 +35,14 @@ fit_powerlaw_tail_optim <- function(object, ...) { #' @rdname powerlaw_optim #' @inheritParams get_non_zero_SFS_range -#' @param peak_detection_upper_limit upper f value up to which the main peak is searched -#' @param reward_upper_limit mutations under the curve up to this limit will be rewarded +#' @param peak_detection_upper_limit Upper f value up to which the main peak is searched +#' @param reward_upper_limit Mutations under the curve up to this limit will be rewarded +#' @param bootstraps Number of bootstrap samples, or NULL to make no resampling #' @export fit_powerlaw_tail_optim.cevodata <- function(object, name = "powerlaw_optim", # pct_left = 0, pct_right = 0.98, + bootstraps = FALSE, allowed_zero_bins = 2, y_treshold = 1, y_threshold_pct = 0.01, @@ -50,10 +52,116 @@ fit_powerlaw_tail_optim.cevodata <- function(object, control = list(maxit = 1000, ndeps = c(0.1, 0.01)), verbose = get_cevomod_verbosity(), ...) { + + if (!bootstraps) { + sfs <- get_SFS(object, name = "SFS") + models <- fit_powerlaw_tail_optim( + sfs, + name = name, + allowed_zero_bins = allowed_zero_bins, + y_treshold = y_treshold, + y_threshold_pct = y_threshold_pct, + av_filter = av_filter, + peak_detection_upper_limit = peak_detection_upper_limit, + reward_upper_limit = reward_upper_limit, + control = control, + verbose = verbose + ) + object$models[[name]] <- models + object <- calc_powerlaw_model_residuals(object, name) + object$active_models <- name + object + } else { + rlang::check_installed("rsample", reason = "to perform bootstrap sampling of SNVs") + splitted_snvs <- SNVs(object) |> + nest_by(.data$sample_id, .keep = TRUE) |> + deframe() |> + map(as_cevo_snvs) + + res <- splitted_snvs |> + map(function(snvs) { + resamples <- snvs |> + rsample::bootstraps(times = bootstraps) + resamples$sfs <- resamples$splits |> + map(rsample::analysis) |> + map(intervalize_mutation_frequencies) |> + map(calc_SFS) + resamples$models <- resamples$sfs |> + map(~fit_powerlaw_tail_optim( + .x, + name = name, + allowed_zero_bins = allowed_zero_bins, + y_treshold = y_treshold, + y_threshold_pct = y_threshold_pct, + av_filter = av_filter, + peak_detection_upper_limit = peak_detection_upper_limit, + reward_upper_limit = reward_upper_limit, + control = control, + verbose = verbose + )) + resamples$tidy_models <- resamples$models |> + map(~pivot_longer(.x, all_of(c("A", "alpha")), names_to = "term", values_to = "estimate")) + + conf_intervals <- rsample::int_pctl(resamples, tidy_models) + + model_params_wide <- conf_intervals |> + pivot_wider( + names_from = "term", + values_from = ".lower":".upper", + names_glue = "{term}{.value}", + names_vary = "slowest" + ) |> + transmute( + A = A.estimate, + A.lower, A.upper, + alpha = alpha.estimate, + alpha.lower, alpha.upper + ) + + res <- list() + res$bootstrap_models <- resamples$models |> + set_names(resamples$id) |> + bind_rows(.id = "resample_id") + res$models <- res$bootstrap_models |> + select("sample_id":"component") |> + unique() |> + cbind(model_params_wide) + res + }) + bootstrap_models <- res |> + map("bootstrap_models") |> + bind_rows(.id = "sample_id") + models <- res |> + map("models") |> + bind_rows(.id = "sample_id") + bootstrap_name <- str_c(name, "_bootstraps") + object$models[[bootstrap_name]] <- bootstrap_models + object$models[[name]] <- models + object <- calc_powerlaw_model_residuals(object, name) + object$active_models <- name + object + } +} + + + +#' @rdname powerlaw_optim +#' @export +fit_powerlaw_tail_optim.cevo_SFS_tbl <- function(object, + name = "powerlaw_optim", + allowed_zero_bins = 2, + y_treshold = 1, + y_threshold_pct = 0.01, + av_filter = c(1/3, 1/3, 1/3), + peak_detection_upper_limit = 0.3, + reward_upper_limit = 0.4, + control = list(maxit = 1000, ndeps = c(0.1, 0.01)), + verbose = get_cevomod_verbosity(), + ...) { msg("Fitting optimized power-law models...", verbose = verbose) start_time <- Sys.time() - sfs <- get_SFS(object, name = "SFS") + sfs <- object bounds <- sfs |> get_non_zero_SFS_range( allowed_zero_bins = allowed_zero_bins, @@ -109,14 +217,11 @@ fit_powerlaw_tail_optim.cevodata <- function(object, class(models) <- c("cevo_powerlaw_models", class(models)) msg("Models fitted in ", Sys.time() - start_time, " seconds", verbose = verbose) - - object$models[[name]] <- models - object <- calc_powerlaw_model_residuals(object, name) - object$active_models <- name - object + models } + td_optim <- function(init_A, init_alpha, data, peak_detection_upper_limit = 0.3, reward_upper_limit = 0.4, diff --git a/man/powerlaw_optim.Rd b/man/powerlaw_optim.Rd index ca874d50..f42d4e0c 100644 --- a/man/powerlaw_optim.Rd +++ b/man/powerlaw_optim.Rd @@ -4,11 +4,27 @@ \alias{powerlaw_optim} \alias{fit_powerlaw_tail_optim} \alias{fit_powerlaw_tail_optim.cevodata} -\title{Fitting Tung Durrett models} +\alias{fit_powerlaw_tail_optim.cevo_SFS_tbl} +\title{Fitting power-law tails with aptimum exponent value} \usage{ fit_powerlaw_tail_optim(object, ...) \method{fit_powerlaw_tail_optim}{cevodata}( + object, + name = "powerlaw_optim", + bootstraps = NULL, + allowed_zero_bins = 2, + y_treshold = 1, + y_threshold_pct = 0.01, + av_filter = c(1/3, 1/3, 1/3), + peak_detection_upper_limit = 0.3, + reward_upper_limit = 0.4, + control = list(maxit = 1000, ndeps = c(0.1, 0.01)), + verbose = get_cevomod_verbosity(), + ... +) + +\method{fit_powerlaw_tail_optim}{cevo_SFS_tbl}( object, name = "powerlaw_optim", allowed_zero_bins = 2, @@ -29,6 +45,8 @@ fit_powerlaw_tail_optim(object, ...) \item{name}{name in the models' slot} +\item{bootstraps}{Number of bootstrap samples, or NULL to make no resampling} + \item{allowed_zero_bins}{number of allowed empty bins in the interval} \item{y_treshold}{bins with less mutations will be considered empty} @@ -38,9 +56,9 @@ height of the higherst peak will be considered empty} \item{av_filter}{average filter values to be applied to f} -\item{peak_detection_upper_limit}{upper f value up to which the main peak is searched} +\item{peak_detection_upper_limit}{Upper f value up to which the main peak is searched} -\item{reward_upper_limit}{mutations under the curve up to this limit will be rewarded} +\item{reward_upper_limit}{Mutations under the curve up to this limit will be rewarded} \item{control}{control param of stats::optim()} diff --git a/tests/testthat/test-fit_powerlaw_tail_optim.R b/tests/testthat/test-fit_powerlaw_tail_optim.R index a28082ab..98f2b0e4 100644 --- a/tests/testthat/test-fit_powerlaw_tail_optim.R +++ b/tests/testthat/test-fit_powerlaw_tail_optim.R @@ -13,6 +13,7 @@ av_filter <- c(1/3, 1/3, 1/3) peak_detection_upper_limit <- 0.3 reward_upper_limit <- 0.4 control <- list(maxit = 1000, ndeps = c(0.1, 0.01)) +verbose <- get_cevomod_verbosity() test_that("fit_powerlaw_tail_optim models have non-negative objective fun value", { From 40a65a78a89089e7b631875895c2917ec16e703f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 12:22:11 +0200 Subject: [PATCH 04/25] verbose_down() implemented --- R/utils.R | 11 +++++++++++ 1 file changed, 11 insertions(+) diff --git a/R/utils.R b/R/utils.R index baa8e60e..bca29ac9 100644 --- a/R/utils.R +++ b/R/utils.R @@ -45,6 +45,17 @@ msg <- function(..., } +verbose_down <- function(verbose) { + if (isTRUE(verbose) || verbose == 0) { + FALSE + } else if (is.numeric(verbose) && verbose > 0) { + verbose - 1 + } else { + stop("Verbose should be logical or positive") + } +} + + require_packages <- function(...) { pkgs <- list(...) missing <- !map_lgl(pkgs, requireNamespace, quietly = TRUE) From 10c25ab154fae44bd5675a867644d8d4e224f6fd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 12:28:54 +0200 Subject: [PATCH 05/25] calc_SFS_resamples() implemented and tested --- R/stat_SFS.R | 29 +++++++++++++++++++++++++++++ tests/testthat/test-stat_SFS.R | 34 ++++++++++++++++++++++++++++++++++ 2 files changed, 63 insertions(+) diff --git a/R/stat_SFS.R b/R/stat_SFS.R index 58cd94f1..c6b76ba9 100644 --- a/R/stat_SFS.R +++ b/R/stat_SFS.R @@ -81,6 +81,35 @@ calc_SFS.cevo_snvs <- function(object, } +calc_SFS_resamples <- function(cd, times, verbose = get_cevomod_verbosity()) { + rlang::check_installed("rsample", reason = "to perform bootstrap sampling of SNVs") + msg("Resampling SNVs and calculating SFSs", verbose = verbose) + + splitted_snvs <- SNVs(cd) |> + nest_by(.data$sample_id, .keep = TRUE) |> + deframe() |> + map(as_cevo_snvs) + + pb <- if (verbose) progress_bar$new(total = length(splitted_snvs)) else NULL + pass_verbose <- verbose_down(verbose) + + resamples <- splitted_snvs |> + map(function(snvs) { + if (!is.null(pb)) pb$tick() + resamples <- rsample::bootstraps(snvs, times = times) + resamples$sfs <- resamples$splits |> + map(rsample::analysis) |> + map(intervalize_mutation_frequencies, verbose = pass_verbose) |> + map(calc_SFS, verbose = pass_verbose) + resamples$splits <- NULL + class(resamples) <- c("cevo_SFS_bootstraps", class(resamples)) + resamples + }) + + resamples +} + + #' @describeIn sfs Plot SFS #' @export plot_SFS <- function(object, ...) { diff --git a/tests/testthat/test-stat_SFS.R b/tests/testthat/test-stat_SFS.R index b53b2bab..43066f65 100644 --- a/tests/testthat/test-stat_SFS.R +++ b/tests/testthat/test-stat_SFS.R @@ -13,6 +13,40 @@ test_that("Calculation of SFS works", { }) + +test_that("Calculation of SFS with resampling works", { + object <- test_data + sfs_resamples <- calc_SFS_resamples(object, times = 2) + + expect_type(sfs_resamples, "list") + expect_equal(length(sfs_resamples), 4) + + sfs_resamples |> + walk(expect_s3_class, "cevo_SFS_bootstraps") + + attribs <- attributes(sfs_resamples$`Sample 1`$sfs[[1]]) + expect_equal(attribs$f_column, "VAF") +}) + + + +test_that("Calculation of SFS with resampling works with CCF/2", { + object <- test_data |> + calc_mutation_frequencies() + sfs_resamples <- calc_SFS_resamples(object, times = 2) + + expect_type(sfs_resamples, "list") + expect_equal(length(sfs_resamples), 4) + + sfs_resamples |> + walk(expect_s3_class, "cevo_SFS_bootstraps") + + attribs <- attributes(sfs_resamples$`Sample 1`$sfs[[1]]) + expect_equal(attribs$f_column, "CCF/2") +}) + + + test_that("plot(calc_SFS()) works", { dt <- SNVs(test_data) expect_warning({ From 51956b61073a5d4769ef4b75b3e65154990760cb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 12:33:23 +0200 Subject: [PATCH 06/25] bootstrap v2 --- NAMESPACE | 1 + R/fit_powerlaw_tail_optim.R | 141 ++++++++++-------- man/powerlaw_optim.Rd | 17 ++- tests/testthat/test-fit_powerlaw_tail_optim.R | 58 +++++-- 4 files changed, 147 insertions(+), 70 deletions(-) diff --git a/NAMESPACE b/NAMESPACE index 508b09fb..fcf2e33c 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -26,6 +26,7 @@ S3method(evaluate_MC_runs,matrix) S3method(filter,cevodata) S3method(fit_mobster,cevodata) S3method(fit_powerlaw_tail_fixed,cevodata) +S3method(fit_powerlaw_tail_optim,cevo_SFS_bootstraps) S3method(fit_powerlaw_tail_optim,cevo_SFS_tbl) S3method(fit_powerlaw_tail_optim,cevodata) S3method(get_CNVs_var_names,cevodata) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index 93dd4528..cb8f4558 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -52,7 +52,6 @@ fit_powerlaw_tail_optim.cevodata <- function(object, control = list(maxit = 1000, ndeps = c(0.1, 0.01)), verbose = get_cevomod_verbosity(), ...) { - if (!bootstraps) { sfs <- get_SFS(object, name = "SFS") models <- fit_powerlaw_tail_optim( @@ -73,67 +72,30 @@ fit_powerlaw_tail_optim.cevodata <- function(object, object } else { rlang::check_installed("rsample", reason = "to perform bootstrap sampling of SNVs") - splitted_snvs <- SNVs(object) |> - nest_by(.data$sample_id, .keep = TRUE) |> - deframe() |> - map(as_cevo_snvs) - - res <- splitted_snvs |> - map(function(snvs) { - resamples <- snvs |> - rsample::bootstraps(times = bootstraps) - resamples$sfs <- resamples$splits |> - map(rsample::analysis) |> - map(intervalize_mutation_frequencies) |> - map(calc_SFS) - resamples$models <- resamples$sfs |> - map(~fit_powerlaw_tail_optim( - .x, - name = name, - allowed_zero_bins = allowed_zero_bins, - y_treshold = y_treshold, - y_threshold_pct = y_threshold_pct, - av_filter = av_filter, - peak_detection_upper_limit = peak_detection_upper_limit, - reward_upper_limit = reward_upper_limit, - control = control, - verbose = verbose - )) - resamples$tidy_models <- resamples$models |> - map(~pivot_longer(.x, all_of(c("A", "alpha")), names_to = "term", values_to = "estimate")) - - conf_intervals <- rsample::int_pctl(resamples, tidy_models) - - model_params_wide <- conf_intervals |> - pivot_wider( - names_from = "term", - values_from = ".lower":".upper", - names_glue = "{term}{.value}", - names_vary = "slowest" - ) |> - transmute( - A = A.estimate, - A.lower, A.upper, - alpha = alpha.estimate, - alpha.lower, alpha.upper - ) - - res <- list() - res$bootstrap_models <- resamples$models |> - set_names(resamples$id) |> - bind_rows(.id = "resample_id") - res$models <- res$bootstrap_models |> - select("sample_id":"component") |> - unique() |> - cbind(model_params_wide) - res - }) - bootstrap_models <- res |> + sfs_resamples <- calc_SFS_resamples(object, times = bootstraps, verbose = verbose) + + models <- sfs_resamples |> + map( + fit_powerlaw_tail_optim, + name = name, + allowed_zero_bins = allowed_zero_bins, + y_treshold = y_treshold, + y_threshold_pct = y_threshold_pct, + av_filter = av_filter, + peak_detection_upper_limit = peak_detection_upper_limit, + reward_upper_limit = reward_upper_limit, + control = control, + verbose = verbose + ) + + bootstrap_models <- models |> map("bootstrap_models") |> - bind_rows(.id = "sample_id") - models <- res |> + bind_rows() + + models <- models |> map("models") |> bind_rows(.id = "sample_id") + bootstrap_name <- str_c(name, "_bootstraps") object$models[[bootstrap_name]] <- bootstrap_models object$models[[name]] <- models @@ -144,6 +106,67 @@ fit_powerlaw_tail_optim.cevodata <- function(object, } +#' @rdname powerlaw_optim +#' @export +fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, + name = "powerlaw_optim", + allowed_zero_bins = 2, + y_treshold = 1, + y_threshold_pct = 0.01, + av_filter = c(1/3, 1/3, 1/3), + peak_detection_upper_limit = 0.3, + reward_upper_limit = 0.4, + control = list(maxit = 1000, ndeps = c(0.1, 0.01)), + verbose = get_cevomod_verbosity(), + ...) { + msg("Bootstrapping ", unique(object$sfs[[1]]$sample_id), " sample", verbose = verbose) + pb <- if (verbose) progress_bar$new(total = nrow(object)) else NULL + + object$models <- object$sfs |> + map(function(sfs) { + if (!is.null(pb)) pb$tick() + fit_powerlaw_tail_optim( + sfs, + name = name, + allowed_zero_bins = allowed_zero_bins, + y_treshold = y_treshold, + y_threshold_pct = y_threshold_pct, + av_filter = av_filter, + peak_detection_upper_limit = peak_detection_upper_limit, + reward_upper_limit = reward_upper_limit, + control = control, + verbose = verbose - 1 + ) + }) + + object$tidy_models <- object$models |> + map(~pivot_longer(.x, all_of(c("A", "alpha")), names_to = "term", values_to = "estimate")) + + conf_intervals <- rsample::int_pctl(object, tidy_models) + + bootstrap_models <- object$models |> + set_names(object$id) |> + bind_rows(.id = "resample_id") + + models <- conf_intervals |> + pivot_wider( + names_from = "term", + values_from = ".lower":".upper", + names_glue = "{term}{.value}", + names_vary = "slowest" + ) |> + transmute( + model = name, + component = "powerlaw tail", + A = A.estimate, + A.lower, A.upper, + alpha = alpha.estimate, + alpha.lower, alpha.upper + ) + + lst(bootstrap_models, models) +} + #' @rdname powerlaw_optim #' @export diff --git a/man/powerlaw_optim.Rd b/man/powerlaw_optim.Rd index f42d4e0c..1f8d09b0 100644 --- a/man/powerlaw_optim.Rd +++ b/man/powerlaw_optim.Rd @@ -4,6 +4,7 @@ \alias{powerlaw_optim} \alias{fit_powerlaw_tail_optim} \alias{fit_powerlaw_tail_optim.cevodata} +\alias{fit_powerlaw_tail_optim.cevo_SFS_bootstraps} \alias{fit_powerlaw_tail_optim.cevo_SFS_tbl} \title{Fitting power-law tails with aptimum exponent value} \usage{ @@ -12,7 +13,21 @@ fit_powerlaw_tail_optim(object, ...) \method{fit_powerlaw_tail_optim}{cevodata}( object, name = "powerlaw_optim", - bootstraps = NULL, + bootstraps = FALSE, + allowed_zero_bins = 2, + y_treshold = 1, + y_threshold_pct = 0.01, + av_filter = c(1/3, 1/3, 1/3), + peak_detection_upper_limit = 0.3, + reward_upper_limit = 0.4, + control = list(maxit = 1000, ndeps = c(0.1, 0.01)), + verbose = get_cevomod_verbosity(), + ... +) + +\method{fit_powerlaw_tail_optim}{cevo_SFS_bootstraps}( + object, + name = "powerlaw_optim", allowed_zero_bins = 2, y_treshold = 1, y_threshold_pct = 0.01, diff --git a/tests/testthat/test-fit_powerlaw_tail_optim.R b/tests/testthat/test-fit_powerlaw_tail_optim.R index 98f2b0e4..744f1fde 100644 --- a/tests/testthat/test-fit_powerlaw_tail_optim.R +++ b/tests/testthat/test-fit_powerlaw_tail_optim.R @@ -4,19 +4,20 @@ set_cevomod_verbosity(0) object <- tcga_brca_test |> intervalize_mutation_frequencies() -name <- "powerlaw_optim" -bootstraps <- NULL -allowed_zero_bins <- 2 -y_treshold <- 1 -y_threshold_pct <- 0.01 -av_filter <- c(1/3, 1/3, 1/3) -peak_detection_upper_limit <- 0.3 -reward_upper_limit <- 0.4 -control <- list(maxit = 1000, ndeps = c(0.1, 0.01)) -verbose <- get_cevomod_verbosity() test_that("fit_powerlaw_tail_optim models have non-negative objective fun value", { + name <- "powerlaw_optim" + bootstraps <- FALSE + allowed_zero_bins <- 2 + y_treshold <- 1 + y_threshold_pct <- 0.01 + av_filter <- c(1/3, 1/3, 1/3) + peak_detection_upper_limit <- 0.3 + reward_upper_limit <- 0.4 + control <- list(maxit = 1000, ndeps = c(0.1, 0.01)) + verbose <- get_cevomod_verbosity() + object <- fit_powerlaw_tail_optim(object) td <- get_models(object, "powerlaw_optim") expect_true(all(td$value > 1990)) @@ -24,6 +25,42 @@ test_that("fit_powerlaw_tail_optim models have non-negative objective fun value" }) + +test_that("fit_powerlaw_tail_optim() bootstrapping test", { + name <- "powerlaw_optim" + bootstraps <- 2 + allowed_zero_bins <- 2 + y_treshold <- 1 + y_threshold_pct <- 0.01 + av_filter <- c(1/3, 1/3, 1/3) + peak_detection_upper_limit <- 0.3 + reward_upper_limit <- 0.4 + control <- list(maxit = 1000, ndeps = c(0.1, 0.01)) + verbose <- TRUE + object <- object |> + filter(sample_id %in% object$metadata$sample_id[1:2]) + + expect_warning({ + object <- fit_powerlaw_tail_optim(object, bootstraps = bootstraps) + }) + + bootstrap_models <- get_models(object, "powerlaw_optim_bootstraps") + expect_equal(nrow(bootstrap_models), 4) + expect_true(all(bootstrap_models$value > 1990)) + expect_s3_class(bootstrap_models, "cevo_powerlaw_models") + + models <- get_models(object, "powerlaw_optim") + expected_columns <- c( + "sample_id", "model", "component", + "A", "A.lower", "A.upper", "alpha", "alpha.lower", "alpha.upper" + ) + expect_named(models, expected_columns) + expect_equal(nrow(models), 2) + expect_s3_class(models, "cevo_powerlaw_models") +}) + + + test_that("Testing td_objective_function", { object <- tcga_brca_test sfs <- get_SFS(object) @@ -45,3 +82,4 @@ test_that("Testing td_objective_function", { res <- -td_objective_function(params, x, y) expect_true(res > 2000) }) + From 1bcbdad3732c50a6a265c49baacedc4aa7c8fac0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 12:40:29 +0200 Subject: [PATCH 07/25] incorrect verbosity fixed, missing classes added --- R/fit_powerlaw_tail_optim.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index cb8f4558..b597806a 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -135,7 +135,7 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, peak_detection_upper_limit = peak_detection_upper_limit, reward_upper_limit = reward_upper_limit, control = control, - verbose = verbose - 1 + verbose = verbose_down(verbose) ) }) @@ -163,6 +163,7 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, alpha = alpha.estimate, alpha.lower, alpha.upper ) + class(models) <- c("cevo_powerlaw_models", class(models)) lst(bootstrap_models, models) } From 19a205da06385d6d0b2a22feb3fe1a8f9ab3204b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 12:47:43 +0200 Subject: [PATCH 08/25] expected warning in suppressed in test-fit_powerlaw_tail_optim.R --- tests/testthat/test-fit_powerlaw_tail_optim.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/tests/testthat/test-fit_powerlaw_tail_optim.R b/tests/testthat/test-fit_powerlaw_tail_optim.R index 744f1fde..8eff2a6e 100644 --- a/tests/testthat/test-fit_powerlaw_tail_optim.R +++ b/tests/testthat/test-fit_powerlaw_tail_optim.R @@ -40,8 +40,8 @@ test_that("fit_powerlaw_tail_optim() bootstrapping test", { object <- object |> filter(sample_id %in% object$metadata$sample_id[1:2]) - expect_warning({ - object <- fit_powerlaw_tail_optim(object, bootstraps = bootstraps) + suppressWarnings({ + object <- fit_powerlaw_tail_optim(object, bootstraps = bootstraps) }) bootstrap_models <- get_models(object, "powerlaw_optim_bootstraps") From 74fbbc1deab46a189afc3aea63b07f8488576000 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 12:52:25 +0200 Subject: [PATCH 09/25] version up --- DESCRIPTION | 2 +- NEWS.md | 3 +++ README.md | 1 + 3 files changed, 5 insertions(+), 1 deletion(-) diff --git a/DESCRIPTION b/DESCRIPTION index 19ecffb8..977eb369 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,6 +1,6 @@ Package: cevomod Title: Cancer Evolution Models -Version: 2.1.0 +Version: 2.2.0 Authors@R: person("Paweł", "Kuś", , "kpawel2210@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4367-9821")) diff --git a/NEWS.md b/NEWS.md index cae15e17..ae57c0f6 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,4 +1,7 @@ +## cevomod 2.2.0 +* fit_powerlaw_tail_fixed() has a bootstrap option + ## cevomod 2.1.0 * cevomod is integrated with a helper [readthis](https://pawelqs.github.io/readthis/index.html) package, designed for bulk reading of variant files from algorithms such as Mutect2, Strelka, ASCAT, or FACETS, in the cevomod-friendly data format. Objects returned by `readthis::read_*()` functions can be added to the cevodata object using a general `add_data()` function. diff --git a/README.md b/README.md index c1407d6e..01a00470 100644 --- a/README.md +++ b/README.md @@ -27,6 +27,7 @@ devtools::install_github("pawelqs/cevomod") ## Last changes +* **v2.2.0** - fit_powerlaw_tail_fixed() has a bootstrap option * **v2.1.0** - cevomod is integrated with a helper [readthis](https://pawelqs.github.io/readthis/index.html) package, designed for bulk reading of variant files from algorithms such as Mutect2, Strelka, ASCAT, or FACETS, in the cevomod-friendly data format. Objects returned by `readthis::read_*()` functions can be added to the cevodata object using a general `add_data()` function. * **v2.0.0** - Starting with version 2.0.0, cevomod can use either VAF or CCF (Cancer Cell Fraction) as a measure of mutation frequency. CCF is a measure of mutation frequency corrected for tumor purity and copy number alterations. CCF can be calculated prior to mutation frequency intervalization using the `calc_mutation_frequencies()` function and requires information on total copy number in tumor and normal tissue and sample purity (tumor cell content). See the Vignettes for more examples. From 9ddfcad525b90ecf237558730f54471594d26111 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 18:39:53 +0200 Subject: [PATCH 10/25] calc_powerllaw_model_residuals() works for bootstrapping results --- R/residuals.R | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/R/residuals.R b/R/residuals.R index 258c3f9a..43aabd17 100644 --- a/R/residuals.R +++ b/R/residuals.R @@ -19,7 +19,7 @@ calc_powerlaw_model_residuals <- function(object, models_name, ...) { from_to_cols_present <- all(c("from", "to") %in% optional_cols) powerlaw_models <- powerlaw_models |> filter(!is.na(.data$A), !is.na(.data$alpha)) |> - select("sample_id", "A", "alpha", all_of(optional_cols)) + select("sample_id", any_of("resample_id"), "A", "alpha", all_of(optional_cols)) sfs <- get_SFS(object) nbins <- summarise(sfs, nbins = n() - 1, .by = "sample_id") # zero bin does not count @@ -30,7 +30,7 @@ calc_powerlaw_model_residuals <- function(object, models_name, ...) { mutate( neutr = if (from_to_cols_present) { .data$f >= .data$from & .data$f <= .data$to - } else NA, + } else NA, ) |> mutate( powerlaw_pred = calc_powerlaw_curve(.data$f, .data$A, .data$alpha, .data$nbins), From 57f18ff18be9cdcbb8f3f1dea219eea3fe4c54a3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Thu, 3 Aug 2023 18:41:43 +0200 Subject: [PATCH 11/25] residuals for bootstrap models are calculated (given tha base SFS) --- R/fit_powerlaw_tail_optim.R | 2 ++ 1 file changed, 2 insertions(+) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index b597806a..0b02170a 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -98,6 +98,7 @@ fit_powerlaw_tail_optim.cevodata <- function(object, bootstrap_name <- str_c(name, "_bootstraps") object$models[[bootstrap_name]] <- bootstrap_models + object <- calc_powerlaw_model_residuals(object, bootstrap_name) object$models[[name]] <- models object <- calc_powerlaw_model_residuals(object, name) object$active_models <- name @@ -147,6 +148,7 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, bootstrap_models <- object$models |> set_names(object$id) |> bind_rows(.id = "resample_id") + class(bootstrap_models) <- c("cevo_bootstrap_powerlaw_models", class(bootstrap_models)) models <- conf_intervals |> pivot_wider( From c75fea94ba0fe5dac12e23e075e4d4730cd913bf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:14:18 +0200 Subject: [PATCH 12/25] test_data_fitted has bootstrapped models --- data-raw/test_data.R | 7 ++++++- data/test_data_fitted.rda | Bin 135900 -> 443794 bytes 2 files changed, 6 insertions(+), 1 deletion(-) diff --git a/data-raw/test_data.R b/data-raw/test_data.R index 41e9de5e..82d3e777 100644 --- a/data-raw/test_data.R +++ b/data-raw/test_data.R @@ -48,7 +48,12 @@ withr::with_seed( fit_powerlaw_tail_fixed() |> fit_subclones() |> fit_powerlaw_tail_optim() |> - fit_subclones() + fit_subclones()# |> + # fit_powerlaw_tail_optim(name = "bs_powerlaw_model", bootstraps = 20) ) +test_data_fitted <- test_data_fitted |> + fit_powerlaw_tail_optim(name = "bs_powerlaw_model", bootstraps = 50) + +test_data_fitted$active_models <- "powerlaw_optim_subclones" use_data(test_data_fitted, overwrite = TRUE) diff --git a/data/test_data_fitted.rda b/data/test_data_fitted.rda index e53fdaaea5cc2af3a6c8d0273958f416e23dfdc1..c9a726fcca5d49ad5c94562837416814bfb3aa80 100644 GIT binary patch delta 376266 zcmaHSV|*pw@9?dSt*xzXZo9Q@+qT2MrLalS_yH|o;OMYPHPjftb!K4_zmWpJzJXomtD)M*D%V!twu4G_x^g*G6#@SM z3IM?P@AwbE1OZUg|1fv}0018F4^#iU@*lV{4&1b{VqyZ&P~pK705fVN6iUKsq6tX| zhU^7uc1a0n05rv-U``rTEKPJQ#Modw03rZ@ieZ}Z|JXT;fdCq-0Cu|;z>n8*=%0000{001mj1ppw<1*zQ!yE{rPFM}fz zsS2oV=1o)aWxCxTyKQJ!YMa`M`EjI`Xviz2Wg4b7F;#c2E-DJZP8Ht`ssBCgKLAfr zQ>1JFq9Fz=gIADaWuir4s3~G#mJR$HgNlL&B$B02&=!CPsDn}p675Jhq$v{cpuhv* z?WzK30}2!ssR5h=%8~Hkp=1Df3@AlKwSV@4hlc_Wv;iO(0#F12FltHwrv?D^KO@>j z6$(OuM*)3F6UjqqQxq|2fkFTPIc!jXlA>ymbOH$g9o*P3%P>appQeHU 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zgy^SM!Nh2fsKZ?O$Mp01j}|uM>ygD*hT5c_?9#s)Vmc*8%Q;(3aPFp%IBk^Jlxs}A zd6D)DDn2@4%x+%;Q#xpfVS#OtgYhGw)%rxa_>s!7T+2>uYQI+NS!WYNsBe*3_1*1= zm`9cT{%R?IhP>8j2Ey(*N@R`^50N}1Y9dCuzJTy|kuSai})WQ!a@s|>}fJ&h$k)XoDFKG##EQ6w>?|MZW+|^L8 z=ww4odZvSr_4I!u%GqjdQ;qHx4x5O>pA`o`%&7BA5*vY>8%j#U<8Q#O^Hb$^bF|epkBMZCx4nK z)cgC=KV~~s4FEM+CEiAP7gO2n;p{2=^IwI3A}$0nvro!ax;T0-a0V`RaPhdI+dp3% zFG&`JXpMlw0vHoQc*(@W84m2+q~OyuvXgNm9EC(|Y$=T4zUWCu*jbD5y)cNvpRK+X z+MBLDvr4J`^JAyvImmxplya=)>R_9q1lSawvZc+B(YZ#ITMv!h9vfiF70A;MhU?5U z$R0ii6_ilE#;lsu%*jkW4-NP}HmKo9YmNB+1PbX7Dz(_e?;>~sKmIP{ig2MJ2Dede D-o5qb From e522db7adb12eb4b0b4f5215935d3fa5c86931fd Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:14:25 +0200 Subject: [PATCH 13/25] Update stat_SFS.R --- R/stat_SFS.R | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/R/stat_SFS.R b/R/stat_SFS.R index c6b76ba9..0769b89b 100644 --- a/R/stat_SFS.R +++ b/R/stat_SFS.R @@ -83,13 +83,14 @@ calc_SFS.cevo_snvs <- function(object, calc_SFS_resamples <- function(cd, times, verbose = get_cevomod_verbosity()) { rlang::check_installed("rsample", reason = "to perform bootstrap sampling of SNVs") - msg("Resampling SNVs and calculating SFSs", verbose = verbose) + msg("Splitting SNVs by sample_id", verbose = verbose) splitted_snvs <- SNVs(cd) |> nest_by(.data$sample_id, .keep = TRUE) |> deframe() |> map(as_cevo_snvs) + msg("Resampling SNVs and calculating SFSs", verbose = verbose) pb <- if (verbose) progress_bar$new(total = length(splitted_snvs)) else NULL pass_verbose <- verbose_down(verbose) From 9bc6a261cc5cf1ef89f980acff4a226a7310bf8d Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:15:04 +0200 Subject: [PATCH 14/25] Plot models can plot bootstrapped powerlaw models --- R/plot_models.R | 174 +++-- man/plot_models.Rd | 27 +- .../bs-powerlaw-model-bootstraps.svg | 593 ++++++++++++++++++ .../plot_models/powerlaw-optim-subclones.svg | 419 +++++++++++++ tests/testthat/test-plot_models.R | 53 +- 5 files changed, 1191 insertions(+), 75 deletions(-) create mode 100644 tests/testthat/_snaps/plot_models/bs-powerlaw-model-bootstraps.svg create mode 100644 tests/testthat/_snaps/plot_models/powerlaw-optim-subclones.svg diff --git a/R/plot_models.R b/R/plot_models.R index 874b1f1d..a7b60a37 100644 --- a/R/plot_models.R +++ b/R/plot_models.R @@ -10,6 +10,7 @@ #' @name plot_models + #' @rdname plot_models #' @export plot_models <- function(object, ...) { @@ -17,14 +18,14 @@ plot_models <- function(object, ...) { } + #' @rdname plot_models -#' @param neutral_tail_alpha 0.3 -#' @param neutral_tail_size 0.5 -#' @param neutral_tail_fill "white" -#' @param neutral_tail_color "gray90" -#' @param binomial_layer_color "black" -#' @param final_fit_color "red" -#' @param final_fit_size 1 +#' @param params_neutral_tail List of non-default params for neutral tail geom +#' @param params_bootstraps List of non-default params for neutral tail bootstraps +#' geom +#' @param params_binomial List of non-default params for binomial geom +#' @param params_subclones List of non-default params for subclones geom +#' @param params_final_fit List of non-default params for final fit geom #' @param nrow passed to facet_wrap #' @param ncol passed to facet_wrap #' @export @@ -34,73 +35,38 @@ plot_models.cevodata <- function(object, show_binomial_layer = FALSE, show_subclones = TRUE, show_final_fit = TRUE, - neutral_tail_alpha = 0.3, - neutral_tail_size = 0.5, - neutral_tail_fill = "white", - neutral_tail_color = "gray90", - binomial_layer_color = "black", - final_fit_color = "red", - final_fit_size = 1, + params_neutral_tail = list(), + params_bootstraps = list(), + params_binomial = list(), + params_subclones = list(), + params_final_fit = list(), nrow = NULL, ncol = NULL, ...) { - models <- get_models(object, models_name) neutral_lm_fitted <- "alpha" %in% names(models) subclones_fitted <- "cellularity" %in% names(models) + bootstraped <- "cevo_bootstrap_powerlaw_models" %in% class(models) resid <- get_residuals(object, models_name) |> left_join(object$metadata, by = "sample_id") |> mutate(sample_id = parse_factor(.data$sample_id, levels = object$metadata$sample_id)) |> - group_by(.data$sample_id) |> - mutate( - ylim = max(.data$SFS) * 1.2, - powerlaw_pred = case_when( - .data$powerlaw_pred > .data$ylim ~ Inf, - .data$f < 0 ~ Inf, - TRUE ~ .data$powerlaw_pred - ) - ) |> - ungroup() + trim_powerlaw_pred() model_layers <- list( - if (show_neutral_tail && neutral_lm_fitted) { - geom_area( - aes(.data$f, .data$powerlaw_pred), - data = resid, - fill = neutral_tail_fill, color = neutral_tail_color, - alpha = neutral_tail_alpha, - size = neutral_tail_size, show.legend = FALSE, - stat = "identity" - ) + if (show_neutral_tail && neutral_lm_fitted && !bootstraped) { + geom_area_neutral_tail(resid, params_neutral_tail) + }, + if (show_neutral_tail && neutral_lm_fitted && bootstraped) { + geom_line_bootstraps(resid, params_bootstraps) }, if (show_binomial_layer && subclones_fitted) { - geom_line( - aes(.data$f, .data$binom_pred), - data = resid, - size = 1, color = binomial_layer_color, linetype = "dashed" - ) + geom_line_binomial(resid, params_binomial) }, if (show_subclones && subclones_fitted) { - dt <- resid |> - pivot_longer( - cols = c("Clone", starts_with("Subclone")), - names_to = "component", - values_to = "pred" - ) |> - filter(!is.na(.data$pred)) - geom_area( - aes(.data$f, .data$pred, group = .data$component), - data = dt, - position = "identity", - size = 1, alpha = 0.3, color = "black", show.legend = FALSE - ) + geom_are_subclones(resid, params_subclones) }, if (show_final_fit && neutral_lm_fitted && subclones_fitted) { - geom_line( - aes(.data$f, .data$model_pred), - data = resid |> filter(.data$powerlaw_pred < .data$ylim), - size = final_fit_size, color = final_fit_color - ) + geom_line_final_fit(resid, params_final_fit) } ) @@ -110,6 +76,100 @@ plot_models.cevodata <- function(object, } + +trim_powerlaw_pred <- function(resid, limit = 1.2) { + resid |> + group_by(.data$sample_id) |> + mutate( + ylim = max(.data$SFS) * limit, + powerlaw_pred = case_when( + .data$powerlaw_pred > .data$ylim ~ Inf, + .data$f < 0 ~ Inf, + TRUE ~ .data$powerlaw_pred + ) + ) |> + ungroup() +} + + +geom_area_neutral_tail <- function(resid, params = list()) { + geom_area( + aes(.data$f, .data$powerlaw_pred), + data = resid, + fill = if (is.null(params$fill)) "white" else params$fill, + color = if (is.null(params$color)) "gray90" else params$color, + alpha = if (is.null(params$alpha)) 0.3 else params$alpha, + size = if (is.null(params$size)) 0.5 else params$size, + show.legend = FALSE, + stat = "identity" + ) +} + + + +geom_line_bootstraps <- function(resid, params = list()) { + geom_line( + aes(.data$f, .data$powerlaw_pred, group = .data$resample_id), + data = resid, + alpha = if (is.null(params$alpha)) 1 else params$alpha, + color = if (is.null(params$color)) "white" else params$color, + linetype = if (is.null(params$linetype)) "solid" else params$linetype, + linewidth = if (is.null(params$linewidth)) 0.3 else params$linewidth, + show.legend = FALSE, + stat = "identity" + ) +} + + + +geom_line_binomial <- function(resid, params = list()) { + geom_line( + aes(.data$f, .data$binom_pred), + data = resid, + alpha = if (is.null(params$alpha)) 1 else params$alpha, + color = if (is.null(params$color)) "black" else params$color, + linetype = if (is.null(params$linetype)) "dashed" else params$linetype, + linewidth = if (is.null(params$linewidth)) 1 else params$linewidth, + ) +} + + + +geom_are_subclones <- function(resid, params) { + dt <- resid |> + pivot_longer( + cols = c("Clone", starts_with("Subclone")), + names_to = "component", + values_to = "pred" + ) |> + filter(!is.na(.data$pred)) + geom_area( + aes(.data$f, .data$pred, group = .data$component), + data = dt, + position = "identity", + alpha = if (is.null(params$alpha)) 0.3 else params$alpha, + color = if (is.null(params$color)) "black" else params$color, + linetype = if (is.null(params$linetype)) "solid" else params$linetype, + linewidth = if (is.null(params$linewidth)) 1 else params$linewidth, + show.legend = FALSE + ) +} + + + +geom_line_final_fit <- function(resid, params) { + geom_line( + aes(.data$f, .data$model_pred), + data = resid |> filter(.data$powerlaw_pred < .data$ylim), + alpha = if (is.null(params$alpha)) 1 else params$alpha, + color = if (is.null(params$color)) "red" else params$color, + linetype = if (is.null(params$linetype)) "solid" else params$linetype, + linewidth = if (is.null(params$linewidth)) 1 else params$linewidth + ) +} + + + plot_clones <- function(clones) { clones |> get_binomial_predictions() |> diff --git a/man/plot_models.Rd b/man/plot_models.Rd index ef93d281..45a2c9d8 100644 --- a/man/plot_models.Rd +++ b/man/plot_models.Rd @@ -14,13 +14,11 @@ plot_models(object, ...) show_binomial_layer = FALSE, show_subclones = TRUE, show_final_fit = TRUE, - neutral_tail_alpha = 0.3, - neutral_tail_size = 0.5, - neutral_tail_fill = "white", - neutral_tail_color = "gray90", - binomial_layer_color = "black", - final_fit_color = "red", - final_fit_size = 1, + params_neutral_tail = list(), + params_bootstraps = list(), + params_binomial = list(), + params_subclones = list(), + params_final_fit = list(), nrow = NULL, ncol = NULL, ... @@ -41,19 +39,16 @@ plot_models(object, ...) \item{show_final_fit}{TRUE,} -\item{neutral_tail_alpha}{0.3} +\item{params_neutral_tail}{List of non-default params for neutral tail geom} -\item{neutral_tail_size}{0.5} +\item{params_bootstraps}{List of non-default params for neutral tail bootstraps +geom} -\item{neutral_tail_fill}{"white"} +\item{params_binomial}{List of non-default params for binomial geom} -\item{neutral_tail_color}{"gray90"} +\item{params_subclones}{List of non-default params for subclones geom} -\item{binomial_layer_color}{"black"} - -\item{final_fit_color}{"red"} - -\item{final_fit_size}{1} +\item{params_final_fit}{List of non-default params for final fit geom} \item{nrow}{passed to facet_wrap} diff --git a/tests/testthat/_snaps/plot_models/bs-powerlaw-model-bootstraps.svg b/tests/testthat/_snaps/plot_models/bs-powerlaw-model-bootstraps.svg new file mode 100644 index 00000000..56cd908e --- /dev/null +++ b/tests/testthat/_snaps/plot_models/bs-powerlaw-model-bootstraps.svg @@ -0,0 +1,593 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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+ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Sample 3 + + + + + + + + + + +Sample 4 + + + + + + + + + + +Sample 1 + + + + + + + + + + +Sample 2 + + + + + + + +0.00 +0.25 +0.50 +0.75 +1.00 + + + + + +0.00 +0.25 +0.50 +0.75 +1.00 +0 +500 +1000 + + + +0 +200 +400 +600 + + + + +0 +100 +200 +300 +400 +500 + + + + + + +0 +200 +400 + + + +VAF +count +SFS + + diff --git a/tests/testthat/test-plot_models.R b/tests/testthat/test-plot_models.R index 93acc2eb..740c003a 100644 --- a/tests/testthat/test-plot_models.R +++ b/tests/testthat/test-plot_models.R @@ -2,6 +2,57 @@ data("tcga_brca_test") set_cevomod_verbosity(0) +test_that("plot_models() works for powerlaw_optim_subclones", { + models_name <- "powerlaw_optim_subclones" + show_neutral_tail <- TRUE + show_binomial_layer <- FALSE + show_subclones <- TRUE + show_final_fit <- TRUE + neutral_tail_alpha <- 0.3 + neutral_tail_size <- 0.5 + neutral_tail_fill <- "white" + neutral_tail_color <- "red"#"gray90" + binomial_layer_color <- "black" + final_fit_color <- "red" + final_fit_size <- 1 + nrow <- NULL + ncol <- NULL + + suppressWarnings({ + p <- plot_models(test_data_fitted, models_name = "powerlaw_optim_subclones") + }) + expect_s3_class(p, c("gg", "ggplot")) + vdiffr::expect_doppelganger("powerlaw_optim_subclones", p) +}) + + + +test_that("plot_models() works for bs_powerlaw_model_bootstraps", { + models_name <- "bs_powerlaw_model_bootstraps" + show_neutral_tail <- TRUE + show_binomial_layer <- FALSE + show_subclones <- TRUE + show_final_fit <- TRUE + neutral_tail_alpha <- 0.3 + neutral_tail_size <- 0.5 + neutral_tail_fill <- "white" + neutral_tail_color <- "red"#"gray90" + binomial_layer_color <- "black" + final_fit_color <- "red" + final_fit_size <- 1 + nrow <- NULL + ncol <- NULL + + + suppressWarnings({ + p <- plot_models(test_data_fitted, models_name = "bs_powerlaw_model_bootstraps") + }) + expect_s3_class(p, c("gg", "ggplot")) + vdiffr::expect_doppelganger("bs_powerlaw_model_bootstraps", p) +}) + + + test_that("Comparing multiple models works", { object <- tcga_brca_test |> fit_powerlaw_tail_fixed() |> @@ -13,5 +64,3 @@ test_that("Comparing multiple models works", { }) expect_s3_class(p, c("gg", "ggplot")) }) - - From 92e4ecb76e9838669bd3421ea1be2f9da68bcd74 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:25:43 +0200 Subject: [PATCH 15/25] R CMD CHECK fixes --- R/fit_powerlaw_tail_optim.R | 10 +++++----- R/prepare_snvs.R | 1 + man/intervalize_mutation_frequencies.Rd | 2 ++ 3 files changed, 8 insertions(+), 5 deletions(-) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index 0b02170a..f1e7e4d7 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -143,7 +143,7 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, object$tidy_models <- object$models |> map(~pivot_longer(.x, all_of(c("A", "alpha")), names_to = "term", values_to = "estimate")) - conf_intervals <- rsample::int_pctl(object, tidy_models) + conf_intervals <- rsample::int_pctl(object, .data$tidy_models) bootstrap_models <- object$models |> set_names(object$id) |> @@ -160,10 +160,10 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, transmute( model = name, component = "powerlaw tail", - A = A.estimate, - A.lower, A.upper, - alpha = alpha.estimate, - alpha.lower, alpha.upper + A = .data$A.estimate, + .data$A.lower, .data$A.upper, + alpha = .data$alpha.estimate, + .data$alpha.lower, .data$alpha.upper ) class(models) <- c("cevo_powerlaw_models", class(models)) diff --git a/R/prepare_snvs.R b/R/prepare_snvs.R index 1a9d5d43..bbc16fd9 100644 --- a/R/prepare_snvs.R +++ b/R/prepare_snvs.R @@ -101,6 +101,7 @@ dentro_2015_correction <- function(tbl) { #' @param column Which frequency measure column to intervalize? By default, uses #' the CCF/2 if it is found in the SNV tibble, and VAF otherwise #' @param bins Number of interval bins +#' @param ... Other args #' @param verbose Verbose? #' #' @return object diff --git a/man/intervalize_mutation_frequencies.Rd b/man/intervalize_mutation_frequencies.Rd index 73c981b5..e0e17072 100644 --- a/man/intervalize_mutation_frequencies.Rd +++ b/man/intervalize_mutation_frequencies.Rd @@ -28,6 +28,8 @@ intervalize_mutation_frequencies(object, ...) \arguments{ \item{object}{\if{html}{\out{}} object} +\item{...}{Other args} + \item{which_snvs}{Which SNVs to use} \item{column}{Which frequency measure column to intervalize? By default, uses From 1d9f1237a65582029b92cff5aed3262b397d22cb Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:55:41 +0200 Subject: [PATCH 16/25] Documentation update --- R/fit_powerlaw_tail_optim.R | 3 ++- R/plot_models.R | 21 ++++++++++++--------- man/plot_models.Rd | 18 +++++++++--------- man/powerlaw_optim.Rd | 3 ++- 4 files changed, 25 insertions(+), 20 deletions(-) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index f1e7e4d7..ec84af8d 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -37,7 +37,8 @@ fit_powerlaw_tail_optim <- function(object, ...) { #' @inheritParams get_non_zero_SFS_range #' @param peak_detection_upper_limit Upper f value up to which the main peak is searched #' @param reward_upper_limit Mutations under the curve up to this limit will be rewarded -#' @param bootstraps Number of bootstrap samples, or NULL to make no resampling +#' @param bootstraps Number of bootstrap samples, or FALSE to make no resampling. +#' **This option significantly extendis the model fitting time!!** #' @export fit_powerlaw_tail_optim.cevodata <- function(object, name = "powerlaw_optim", diff --git a/R/plot_models.R b/R/plot_models.R index a7b60a37..d9268418 100644 --- a/R/plot_models.R +++ b/R/plot_models.R @@ -1,12 +1,14 @@ +## ------------------------- plot_models() function --------------------------- + #' Plot cevodata models -#' @param object cevodata object -#' @param models_name models name -#' @param show_neutral_tail TRUE, -#' @param show_binomial_layer FALSE, -#' @param show_subclones TRUE, -#' @param show_final_fit TRUE, -#' @param ... other arguments passed to plot_SFS() +#' @param object `` object +#' @param models_name Name of the models to plot +#' @param show_neutral_tail `` +#' @param show_binomial_layer `` +#' @param show_subclones `` +#' @param show_final_fit `` +#' @param ... Other arguments passed to plot_SFS() #' @name plot_models @@ -26,8 +28,8 @@ plot_models <- function(object, ...) { #' @param params_binomial List of non-default params for binomial geom #' @param params_subclones List of non-default params for subclones geom #' @param params_final_fit List of non-default params for final fit geom -#' @param nrow passed to facet_wrap -#' @param ncol passed to facet_wrap +#' @param nrow Passed to facet_wrap +#' @param ncol Passed to facet_wrap #' @export plot_models.cevodata <- function(object, models_name = active_models(object), @@ -169,6 +171,7 @@ geom_line_final_fit <- function(resid, params) { } +## --------------------------- Other functions -------------------------------- plot_clones <- function(clones) { clones |> diff --git a/man/plot_models.Rd b/man/plot_models.Rd index 45a2c9d8..6ce14377 100644 --- a/man/plot_models.Rd +++ b/man/plot_models.Rd @@ -25,19 +25,19 @@ plot_models(object, ...) ) } \arguments{ -\item{object}{cevodata object} +\item{object}{\verb{} object} -\item{...}{other arguments passed to plot_SFS()} +\item{...}{Other arguments passed to plot_SFS()} -\item{models_name}{models name} +\item{models_name}{Name of the models to plot} -\item{show_neutral_tail}{TRUE,} +\item{show_neutral_tail}{\verb{}} -\item{show_binomial_layer}{FALSE,} +\item{show_binomial_layer}{\verb{}} -\item{show_subclones}{TRUE,} +\item{show_subclones}{\verb{}} -\item{show_final_fit}{TRUE,} +\item{show_final_fit}{\verb{}} \item{params_neutral_tail}{List of non-default params for neutral tail geom} @@ -50,9 +50,9 @@ geom} \item{params_final_fit}{List of non-default params for final fit geom} -\item{nrow}{passed to facet_wrap} +\item{nrow}{Passed to facet_wrap} -\item{ncol}{passed to facet_wrap} +\item{ncol}{Passed to facet_wrap} } \description{ Plot cevodata models diff --git a/man/powerlaw_optim.Rd b/man/powerlaw_optim.Rd index 1f8d09b0..51d67031 100644 --- a/man/powerlaw_optim.Rd +++ b/man/powerlaw_optim.Rd @@ -60,7 +60,8 @@ fit_powerlaw_tail_optim(object, ...) \item{name}{name in the models' slot} -\item{bootstraps}{Number of bootstrap samples, or NULL to make no resampling} +\item{bootstraps}{Number of bootstrap samples, or FALSE to make no resampling. +\strong{This option significantly extendis the model fitting time!!}} \item{allowed_zero_bins}{number of allowed empty bins in the interval} From 30bc7d675afd994c49795730649bea02c215eae4 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:55:46 +0200 Subject: [PATCH 17/25] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 01a00470..ef3fe93b 100644 --- a/README.md +++ b/README.md @@ -27,7 +27,7 @@ devtools::install_github("pawelqs/cevomod") ## Last changes -* **v2.2.0** - fit_powerlaw_tail_fixed() has a bootstrap option +* **v2.2.0** - fit_powerlaw_tail_fixed() has a bootstrap option. See the details in [Fitting models #Bootstrapping](https://pawelqs.github.io/cevomod/articles/fitting_models.html#bootstrapping) vignette * **v2.1.0** - cevomod is integrated with a helper [readthis](https://pawelqs.github.io/readthis/index.html) package, designed for bulk reading of variant files from algorithms such as Mutect2, Strelka, ASCAT, or FACETS, in the cevomod-friendly data format. Objects returned by `readthis::read_*()` functions can be added to the cevodata object using a general `add_data()` function. * **v2.0.0** - Starting with version 2.0.0, cevomod can use either VAF or CCF (Cancer Cell Fraction) as a measure of mutation frequency. CCF is a measure of mutation frequency corrected for tumor purity and copy number alterations. CCF can be calculated prior to mutation frequency intervalization using the `calc_mutation_frequencies()` function and requires information on total copy number in tumor and normal tissue and sample purity (tumor cell content). See the Vignettes for more examples. From 5d98e087c22475a51021f0c7d13d23d7276ddc5c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 11:55:49 +0200 Subject: [PATCH 18/25] Update fitting_models.Rmd --- vignettes/fitting_models.Rmd | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) diff --git a/vignettes/fitting_models.Rmd b/vignettes/fitting_models.Rmd index 66b47945..f0ebf17f 100644 --- a/vignettes/fitting_models.Rmd +++ b/vignettes/fitting_models.Rmd @@ -104,3 +104,31 @@ cd |> get_selection_coefficients() ``` + +# Bootstrapping + +Since version 2.2.0 `fit_powerlaw_tail_optim()` function has a new `bootstraps` argument which can be either `FALSE` or an integer number indicating the number of bootstrap samples. Bootstrapping is performed using [tidyverse/rsample](https://rsample.tidymodels.org/) package and requires it to be installed. + +**Bootstrapping significantly extends the model fitting time!** + +If `bootstraps` is an integer greater than 1, the SNVs from the default assay are split by sample_id, resampled N times, new SFS spectra are computed, and N models are fitted for each sample. The resampled models are stored in the `_bootstraps` slot (residuals for each resample are stored in the `misc` slot with the same name), and the summarized model with confidence intervals is stored in the `model_name` slot. + +For demonstration purposes, we will bootstrap for 2 samples and with only 2 resamples. + +```{r} +cd <- cd |> + filter(sample_id %in% cd$metadata$sample_id[1:2]) |> + fit_powerlaw_tail_optim(name = "bs_model", bootstraps = 2) + +get_model_names(cd) +``` + +```{r} +get_models(cd, "bs_model_bootstraps") +``` + +```{r} +get_models(cd, "bs_model") +``` + +Resampled models can be plotted in the same way as non-resampled models using the `plot_models()` function. From 8b5149ee5904eb322c3c86b83e99dd77d5947657 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:01:58 +0200 Subject: [PATCH 19/25] verbose message update --- R/fit_powerlaw_tail_optim.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index ec84af8d..8e6887b1 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -121,7 +121,7 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, control = list(maxit = 1000, ndeps = c(0.1, 0.01)), verbose = get_cevomod_verbosity(), ...) { - msg("Bootstrapping ", unique(object$sfs[[1]]$sample_id), " sample", verbose = verbose) + msg("Fitting models to ", unique(object$sfs[[1]]$sample_id), " resamples", verbose = verbose) pb <- if (verbose) progress_bar$new(total = nrow(object)) else NULL object$models <- object$sfs |> From dc8f9b19656762b3a67528077e2de44a4b0be9db Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:21:18 +0200 Subject: [PATCH 20/25] Update test-fit_powerlaw_tail_optim.R --- tests/testthat/test-fit_powerlaw_tail_optim.R | 1 + 1 file changed, 1 insertion(+) diff --git a/tests/testthat/test-fit_powerlaw_tail_optim.R b/tests/testthat/test-fit_powerlaw_tail_optim.R index 8eff2a6e..c25eb958 100644 --- a/tests/testthat/test-fit_powerlaw_tail_optim.R +++ b/tests/testthat/test-fit_powerlaw_tail_optim.R @@ -48,6 +48,7 @@ test_that("fit_powerlaw_tail_optim() bootstrapping test", { expect_equal(nrow(bootstrap_models), 4) expect_true(all(bootstrap_models$value > 1990)) expect_s3_class(bootstrap_models, "cevo_powerlaw_models") + expect_s3_class(bootstrap_models, "cevo_bootstrap_powerlaw_models") models <- get_models(object, "powerlaw_optim") expected_columns <- c( From 407dff3aa2a685756f7644a93e215f1acd98d121 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:23:03 +0200 Subject: [PATCH 21/25] Unused params removed from test-plot_models.R --- tests/testthat/test-plot_models.R | 14 -------------- 1 file changed, 14 deletions(-) diff --git a/tests/testthat/test-plot_models.R b/tests/testthat/test-plot_models.R index 740c003a..d2cff791 100644 --- a/tests/testthat/test-plot_models.R +++ b/tests/testthat/test-plot_models.R @@ -8,13 +8,6 @@ test_that("plot_models() works for powerlaw_optim_subclones", { show_binomial_layer <- FALSE show_subclones <- TRUE show_final_fit <- TRUE - neutral_tail_alpha <- 0.3 - neutral_tail_size <- 0.5 - neutral_tail_fill <- "white" - neutral_tail_color <- "red"#"gray90" - binomial_layer_color <- "black" - final_fit_color <- "red" - final_fit_size <- 1 nrow <- NULL ncol <- NULL @@ -33,13 +26,6 @@ test_that("plot_models() works for bs_powerlaw_model_bootstraps", { show_binomial_layer <- FALSE show_subclones <- TRUE show_final_fit <- TRUE - neutral_tail_alpha <- 0.3 - neutral_tail_size <- 0.5 - neutral_tail_fill <- "white" - neutral_tail_color <- "red"#"gray90" - binomial_layer_color <- "black" - final_fit_color <- "red" - final_fit_size <- 1 nrow <- NULL ncol <- NULL From 000a7a83f90aebd143f7776c6542e1b03c58581b Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:23:34 +0200 Subject: [PATCH 22/25] Update test-plot_models.R --- tests/testthat/test-plot_models.R | 1 - 1 file changed, 1 deletion(-) diff --git a/tests/testthat/test-plot_models.R b/tests/testthat/test-plot_models.R index d2cff791..8536c0fa 100644 --- a/tests/testthat/test-plot_models.R +++ b/tests/testthat/test-plot_models.R @@ -29,7 +29,6 @@ test_that("plot_models() works for bs_powerlaw_model_bootstraps", { nrow <- NULL ncol <- NULL - suppressWarnings({ p <- plot_models(test_data_fitted, models_name = "bs_powerlaw_model_bootstraps") }) From c25a4a997fede46df01b03aabc093d1f0673b72c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:25:55 +0200 Subject: [PATCH 23/25] rsample pkg required in fit_powerlaw_tail_optim.cevo_SFS_bootstraps() --- R/fit_powerlaw_tail_optim.R | 1 + 1 file changed, 1 insertion(+) diff --git a/R/fit_powerlaw_tail_optim.R b/R/fit_powerlaw_tail_optim.R index 8e6887b1..9731fa64 100644 --- a/R/fit_powerlaw_tail_optim.R +++ b/R/fit_powerlaw_tail_optim.R @@ -121,6 +121,7 @@ fit_powerlaw_tail_optim.cevo_SFS_bootstraps <- function(object, control = list(maxit = 1000, ndeps = c(0.1, 0.01)), verbose = get_cevomod_verbosity(), ...) { + rlang::check_installed("rsample", reason = "to perform bootstrap sampling of SNVs") msg("Fitting models to ", unique(object$sfs[[1]]$sample_id), " resamples", verbose = verbose) pb <- if (verbose) progress_bar$new(total = nrow(object)) else NULL From 3417c9f91a5e4fbcd24de9538021cbbdbffcd749 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:27:40 +0200 Subject: [PATCH 24/25] tests for verbose_down() added --- tests/testthat/test-utils.R | 8 ++++++++ 1 file changed, 8 insertions(+) diff --git a/tests/testthat/test-utils.R b/tests/testthat/test-utils.R index 155dfd13..d03a80f2 100644 --- a/tests/testthat/test-utils.R +++ b/tests/testthat/test-utils.R @@ -17,3 +17,11 @@ test_that("segment() function works", { vec <- c(T, T, T, F, F, T, F, F) expect_equal(segment(vec), c(0, 0, 0, 1, 1, 2, 3, 3)) }) + + +test_that("verbose_down() works", { + expect_equal(verbose_down(TRUE), FALSE) + expect_equal(verbose_down(FALSE), FALSE) + expect_equal(verbose_down(2), 1) + expect_equal(verbose_down(3), 2) +}) From 1530f0cb0cf08260571910169f45440f244e0030 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Pawe=C5=82?= Date: Fri, 4 Aug 2023 12:29:22 +0200 Subject: [PATCH 25/25] update verbose_down() --- R/utils.R | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/R/utils.R b/R/utils.R index bca29ac9..cceb9c84 100644 --- a/R/utils.R +++ b/R/utils.R @@ -46,7 +46,7 @@ msg <- function(..., verbose_down <- function(verbose) { - if (isTRUE(verbose) || verbose == 0) { + if (isTRUE(verbose) || isFALSE(verbose) || verbose == 0) { FALSE } else if (is.numeric(verbose) && verbose > 0) { verbose - 1