knitr::opts_chunk$set(echo = params$printcode)
for (i in 1:length(params)) { if (TRUE) { cat(paste0(names(params)[i], ": ", params[[i]], "\n")) } }
devtools::load_all()
idep_data <- idepGolem::get_idep_data() expression_file <- data.frame( datapath = params$YOUR_DATA_PATH ) if (!is.null(params$YOUR_EXPERIMENT_PATH)) { experiment_file <- data.frame( datapath = params$YOUR_EXPERIMENT_PATH ) } else { experiment_file <- NULL }
load_data <- input_data( expression_file = expression_file, experiment_file = experiment_file, go_button = FALSE, demo_data_file = idep_data$demo_data_file, demo_metadata_file = idep_data$demo_metadata_file ) converted <- convert_id( query = rownames(load_data$data), idep_data = idep_data, select_org = "BestMatch" ) all_gene_info <- gene_info( converted = converted, select_org = "BestMatch", idep_data = idep_data ) converted_data <- convert_data( converted = converted, no_id_conversion = params$no_id_conversion, data = load_data$data ) gene_names <- get_all_gene_names( mapped_ids = converted_data$mapped_ids, all_gene_info = all_gene_info )
processed_data <- pre_process( data = converted_data$data, missing_value = params$missing_value, data_file_format = params$data_file_format, low_filter_fpkm = params$low_filter_fpkm, n_min_samples_fpkm = params$n_min_samples_fpkm, log_transform_fpkm = params$log_transform_fpkm, log_start_fpkm = params$log_start_fpkm, min_counts = params$min_counts, n_min_samples_count = params$n_min_samples_count, counts_transform = params$counts_transform, counts_log_start = params$counts_log_start, no_fdr = params$no_fdr ) # processed_data <- pre_process( # data = converted_data$data, # missing_value = "geneMedian", # data_file_format = 1, # low_filter_fpkm = NULL, # n_min_samples_fpkm = NULL, # log_transform_fpkm = NULL, # log_start_fpkm = NULL, # min_counts = .5, # n_min_samples_count = 1, # counts_transform = 1, # counts_log_start = 4, # no_fdr = NULL # )
fig.height=1.5, fig.width=2.5
if (params$data_file_format == 1) { total_counts_ggplot( counts_data = processed_data$raw_counts, sample_info = load_data$sample_info ) }
# colnames(processed_data$data) eda_scatter( processed_data = processed_data$data, # plot_xaxis = "p53_IR_1", # plot_yaxis = "p53_mock_1" plot_yaxis = colnames(processed_data$data)[1], plot_xaxis = colnames(processed_data$data)[2] )
eda_boxplot( processed_data = processed_data$data, sample_info = load_data$sample_info )
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