## ----------------------------------------------------------------------------- library(transite) ## ---- message=FALSE----------------------------------------------------------- background_df <- transite:::ge$background_df ## ---- message=FALSE----------------------------------------------------------- background_df <- dplyr::arrange(background_df, value) ## ---- message=FALSE----------------------------------------------------------- background_set <- gsub("T", "U", background_df$seq) ## ---- message=FALSE----------------------------------------------------------- names(background_set) <- paste0(background_df$refseq, "|", background_df$seq_type) ## ---- message=FALSE----------------------------------------------------------- motif_db <- get_motif_by_id("M178_0.6") ## ---- message=FALSE----------------------------------------------------------- results <- run_matrix_spma(background_set, motifs = motif_db, cache = FALSE) # Usually, all motifs are included in the analysis and results are cached to make subsequent analyses more efficient. # results <- run_matrix_spma(background_set) ## ---- results='asis', echo=FALSE, fig.width=10, fig.height=7------------------ cat("\n\n####", results$spectrum_info_df$motif_rbps, " (", results$spectrum_info_df$motif_id, ")\n\n", sep = "") cat("\n\n**Spectrum plot with polynomial regression:**\n\n") grid::grid.draw(results$spectrum_plots[[1]]) cat("\n\n**Classification:**\n\n") if (results$spectrum_info_df$aggregate_classifier_score == 3) { cat('\n\n

spectrum classification: non-random (3 out of 3 criteria met)

\n\n') } else if (results$spectrum_info_df$aggregate_classifier_score == 2) { cat('\n\n

spectrum classification: random (2 out of 3 criteria met)

\n\n') } else if (results$spectrum_info_df$aggregate_classifier_score == 1) { cat('\n\n

spectrum classification: random (1 out of 3 criteria met)

\n\n') } else { cat('\n\n

spectrum classification: random (0 out of 3 criteria met)

\n\n') } cat("\n\nProperty | Value | Threshold\n") cat("------------- | ------------- | -------------\n") cat("adjusted $R^2$ | ", round(results$spectrum_info_df$adj_r_squared, 3), " | $\\geq 0.4$ \n") cat("polynomial degree | ", results$spectrum_info_df$degree, " | $\\geq 1$ \n") cat("slope | ", round(results$spectrum_info_df$slope, 3), " | $\\neq 0$ \n") cat("unadjusted p-value estimate of consistency score | ", round(results$spectrum_info_df$consistency_score_p_value, 7), " | $< 0.000005$ \n") cat("number of significant bins | ", results$spectrum_info_df$n_significant, " | ", paste0("$\\geq ", floor(40 / 10), "$"), " \n\n")