View source: R/createbarerrorplots.R
createbarerrorplots | R Documentation |
Internal function to create relative-error bar plots.
createbarerrorplots( statstable_pre, statstable_post, rv, type, locus_id = NULL, plotdir, logfilename, mode = NULL, plot_height = 5, plot_width = 7.5, plot_textsize = 16 )
statstable_pre |
A data.table object, containing the output of
|
statstable_post |
A data.table object, containing the output of
|
rv |
A list object. A list that contains additional objects needed for the algorithms. |
type |
A single integer. Type of data to be corrected: either "1" (one locus in many samples, e.g. pyrosequencing data) or "2" (many loci in one sample, e.g. next-generation sequencing data or microarray data). |
locus_id |
A character string. Default: NULL. ID of the respective locus (only used in type 2 correction). |
plotdir |
A character string. Path to the folder, where plots are saved. |
logfilename |
A character string. Path to a file to save the log messages (default = paste0(tempdir(), "/log.txt")). |
mode |
A character string. Default: NULL. Used to indicate "corrected" calibration data. |
plot_height |
A integer value. The height (unit: inch) of the resulting plots (default: 5). |
plot_width |
A integer value. The width (unit: inch) of the resulting plots (default: 7.5). |
plot_textsize |
A integer value. The textsize of the resulting plots (default: 16). |
This function creates error bar-plots to visualize the relative error before and after bias correction and writes these plots to the local filesystem.
# define list object to save all data rv <- list() rv$minmax <- TRUE rv$selection_method <- "RelError" rv$sample_locus_name <- "Test" rv$seed <- 1234 # define plotdir rv$plotdir <- paste0(tempdir(), "/plots/") dir.create(rv$plotdir) # define logfilename logfilename <- paste0(tempdir(), "/log.txt") # import experimental file exp_type_1 <- rBiasCorrection::example.data_experimental rv$fileimport_experimental <- exp_type_1$dat # import calibration file cal_type_1 <- rBiasCorrection::example.data_calibration rv$fileimport_calibration <- cal_type_1$dat rv$vec_cal <- cal_type_1$vec_cal # perform regression regression_results <- regression_utility( rv$fileimport_calibration, "Testlocus", locus_id = NULL, rv = rv, mode = NULL, logfilename, minmax = rv$minmax, seed = rv$seed ) # extract regression results rv$result_list <- regression_results$result_list # get regression statistics rv$reg_stats <- statistics_list( rv$result_list, minmax = TRUE ) # select the better model based on the sum of squared errrors ("SSE") rv$choices_list <- better_model( statstable_pre = rv$reg_stats, selection_method = "SSE" ) # correct calibration data (to show corrected calibration curves) solved_eq_h <- solving_equations(datatable = rv$fileimport_calibration, regmethod = rv$choices_list, type = 1, rv = rv, mode = "corrected", logfilename = logfilename, minmax = rv$minmax) rv$fileimport_cal_corrected_h <- solved_eq_h$results colnames(rv$fileimport_cal_corrected_h) <- colnames( rv$fileimport_calibration ) # calculate new calibration curves from corrected calibration data regression_results <- regression_utility( data = rv$fileimport_cal_corrected_h, samplelocusname = rv$sample_locus_name, rv = rv, mode = "corrected", logfilename = logfilename, minmax = rv$minmax, seed = rv$seed ) rv$result_list_hyperbolic <- regression_results$result_list # save regression statistics to reactive value rv$reg_stats_corrected_h <- statistics_list( resultlist = rv$result_list_hyperbolic, minmax = rv$minmax ) createbarerrorplots( statstable_pre = rv$reg_stats, statstable_post = rv$reg_stats_corrected_h, rv = rv, type = 1, locus_id = NULL, plotdir = rv$plotdir, logfilename = logfilename, mode = "corrected_h", plot_height = 5, plot_width = 7.5, plot_textsize = 1 )
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