plot_assay_stdevs-sigma_block-method: #' @import data.table #' @export #' @include generics.R...

In biospi/deamass: Statistical modelling for mass spectrometry omics

#' @import data.table #' @export #' @include generics.R setMethod("plot_priors", "sigma_block", function( object, data = list( priors(object, as.data.table = T)[is.na(Assay)][, .(Block, Effect, s, df)], priors(object, as.data.table = T)[is.na(Assay)][, .(Block, Effect, s = s0, df = df0)], rbind( measurement_stdevs(object, input = "model0", summary = T, as.data.table = T)[, .(Block, Effect = "Measurements", value = rinaka(length(s), s, df))], component_stdevs(object, input = "model0", summary = T, as.data.table = T)[, .(Block, Effect = "Components", value = rinaka(length(s), s, df))] ) ), horizontal = TRUE, draw_quantiles = list(0.5, NULL, NULL), trim = c(0.05, 0.95), colour = list("blue", "black", NULL), fill = list("lightblue", NULL, "grey"), alpha = list(0.5, 0.5, 0.5), facets = "Block", value.label = "stdev", value.limits = limits_dists(data, trim, c(0, 1), include.zero = T), value.length = 160, variables.labels = TRUE, variable.sort.cols = NULL, variable.label.cols = "Effect", variable.interval = 5, show.legend = TRUE, file = NULL ) return(plot_dists(object, data, horizontal, draw_quantiles, trim, colour, fill, alpha, facets, value.label, value.limits, value.length, variables.labels, variable.sort.cols, variable.label.cols, variable.interval, show.legend, file)) )

Description

#' @import data.table #' @export #' @include generics.R setMethod("plot_priors", "sigma_block", function( object, data = list( priors(object, as.data.table = T)[is.na(Assay)][, .(Block, Effect, s, df)], priors(object, as.data.table = T)[is.na(Assay)][, .(Block, Effect, s = s0, df = df0)], rbind( measurement_stdevs(object, input = "model0", summary = T, as.data.table = T)[, .(Block, Effect = "Measurements", value = rinaka(length(s), s, df))], component_stdevs(object, input = "model0", summary = T, as.data.table = T)[, .(Block, Effect = "Components", value = rinaka(length(s), s, df))] ) ), horizontal = TRUE, draw_quantiles = list(0.5, NULL, NULL), trim = c(0.05, 0.95), colour = list("blue", "black", NULL), fill = list("lightblue", NULL, "grey"), alpha = list(0.5, 0.5, 0.5), facets = "Block", value.label = "stdev", value.limits = limits_dists(data, trim, c(0, 1), include.zero = T), value.length = 160, variables.labels = TRUE, variable.sort.cols = NULL, variable.label.cols = "Effect", variable.interval = 5, show.legend = TRUE, file = NULL ) return(plot_dists(object, data, horizontal, draw_quantiles, trim, colour, fill, alpha, facets, value.label, value.limits, value.length, variables.labels, variable.sort.cols, variable.label.cols, variable.interval, show.legend, file)) )

Usage

## S4 method for signature 'sigma_block'
plot_assay_stdevs(
  object,
  data = list(assay_stdevs(object, as.data.table = T)[, list(Block, Assay, s, df)],
    assay_stdevs(object, as.data.table = T)[, list(Block, Assay, s = B.sC, df = B.dfC)],
    assay_stdevs(object, as.data.table = T)[, list(Block, Assay, s = B.sM, df = B.dfM)]),
  draw_quantiles = list(0.5, NULL, NULL),
  trim = c(0.05, 0.95),
  colour = list("A.qM", NULL, NULL),
  fill = list(NULL, "darkgreen", "black"),
  alpha = list(0.75, 0.2, 0.2),
  value.label = "stdev",
  value.limits = limits_dists(data, trim, include.zero = T, non.negative = T),
  variable.summary.cols = c("Block", "Run", "Channel", "Assay", "RefWeight", "Sample",
    "Condition", "A.qG", "A.qC", "A.qM", "A.qD"),
  variable.label.cols = c("Sample", "Assay", "Block"),
  ...
)

biospi/deamass documentation built on May 20, 2023, 3:30 a.m.