See details for description.
show_sig_bootstrap_exposure( bt_result, sample = NULL, signatures = NULL, methods = "QP", plot_fun = c("boxplot", "violin"), agg_fun = c("mean", "median", "min", "max"), highlight = "auto", highlight_size = 4, palette = "aaas", title = NULL, xlab = FALSE, ylab = "Signature exposure", width = 0.3, dodge_width = 0.8, outlier.shape = NA, add = "jitter", add.params = list(alpha = 0.3), ... ) show_sig_bootstrap_error( bt_result, sample = NULL, methods = "QP", plot_fun = c("boxplot", "violin"), agg_fun = c("mean", "median"), highlight = "auto", highlight_size = 4, palette = "aaas", title = NULL, xlab = FALSE, ylab = "Reconstruction error (L2 norm)", width = 0.3, dodge_width = 0.8, outlier.shape = NA, add = "jitter", add.params = list(alpha = 0.3), legend = "none", ... ) show_sig_bootstrap_stability( bt_result, signatures = NULL, measure = c("RMSE", "CV", "MAE", "AbsDiff"), methods = "QP", plot_fun = c("boxplot", "violin"), palette = "aaas", title = NULL, xlab = FALSE, ylab = "Signature instability", width = 0.3, outlier.shape = NA, add = "jitter", add.params = list(alpha = 0.3), ... )
| bt_result | result object from sig_fit_bootstrap_batch. |
|---|---|
| sample | a sample id. |
| signatures | signatures to show. |
| methods | a subset of |
| plot_fun | set the plot function. |
| agg_fun | set the aggregation function when |
| highlight | set the color for optimal solution. Default is "auto", which use the same color as bootstrap results, you can set it to color like "red", "gold", etc. |
| highlight_size | size for highlighting triangle, default is |
| palette | the color palette to be used for coloring or filling by groups. Allowed values include "grey" for grey color palettes; brewer palettes e.g. "RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and scientific journal palettes from ggsci R package, e.g.: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty". |
| title | plot main title. |
| xlab | character vector specifying x axis labels. Use xlab = FALSE to hide xlab. |
| ylab | character vector specifying y axis labels. Use ylab = FALSE to hide ylab. |
| width | numeric value between 0 and 1 specifying box width. |
| dodge_width | dodge width. |
| outlier.shape | point shape of outlier. Default is 19. To hide outlier,
specify |
| add | character vector for adding another plot element (e.g.: dot plot or error bars). Allowed values are one or the combination of: "none", "dotplot", "jitter", "boxplot", "point", "mean", "mean_se", "mean_sd", "mean_ci", "mean_range", "median", "median_iqr", "median_hilow", "median_q1q3", "median_mad", "median_range"; see ?desc_statby for more details. |
| add.params | parameters (color, shape, size, fill, linetype) for the argument 'add'; e.g.: add.params = list(color = "red"). |
| ... | other parameters passing to ggpubr::ggboxplot or ggpubr::ggviolin. |
| legend | character specifying legend position. Allowed values are one of c("top", "bottom", "left", "right", "none"). To remove the legend use legend = "none". Legend position can be also specified using a numeric vector c(x, y); see details section. |
| measure | measure to estimate the exposure instability, can be one of 'RMSE', 'CV', 'MAE' and 'AbsDiff'. |
a ggplot object
Functions:
show_sig_bootstrap_exposure - this function plots exposures from bootstrap samples with both dotted boxplot. The optimal exposure (the exposure from original input) is shown as triangle point. Only one sample can be plotted.
show_sig_bootstrap_error - this function plots decomposition errors from bootstrap samples with both dotted boxplot. The error from optimal solution (the decomposition error from original input) is shown as triangle point. Only one sample can be plotted.
show_sig_bootstrap_stability - this function plots the signature exposure instability for specified signatures. Currently, the instability measure supports 3 types:
'RMSE' for Mean Root Squared Error (default) of bootstrap exposures and original exposures for each sample.
'CV' for Coefficient of Variation (CV) based on RMSE (i.e. RMSE / btExposure_mean).
'MAE' for Mean Absolute Error of bootstrap exposures and original exposures for each sample.
'AbsDiff' for Absolute Difference between mean bootstram exposure and original exposure.
Huang X, Wojtowicz D, Przytycka TM. Detecting presence of mutational signatures in cancer with confidence. Bioinformatics. 2018;34(2):330–337. doi:10.1093/bioinformatics/btx604
# \donttest{ if (require("BSgenome.Hsapiens.UCSC.hg19")) { laml.maf <- system.file("extdata", "tcga_laml.maf.gz", package = "maftools") laml <- read_maf(maf = laml.maf) mt_tally <- sig_tally( laml, ref_genome = "BSgenome.Hsapiens.UCSC.hg19", use_syn = TRUE ) library(NMF) mt_sig <- sig_extract(mt_tally$nmf_matrix, n_sig = 3, nrun = 2, cores = 1 ) mat <- t(mt_tally$nmf_matrix) mat <- mat[, colSums(mat) > 0] bt_result <- sig_fit_bootstrap_batch(mat, sig = mt_sig, n = 10) ## Parallel computation ## bt_result = sig_fit_bootstrap_batch(mat, sig = mt_sig, n = 10, use_parallel = TRUE) ## At default, mean bootstrap exposure for each sample has been calculated p <- show_sig_bootstrap_exposure(bt_result, methods = c("QP")) ## Show bootstrap exposure (optimal exposure is shown as triangle) p1 <- show_sig_bootstrap_exposure(bt_result, methods = c("QP"), sample = "TCGA-AB-2802") p1 p2 <- show_sig_bootstrap_exposure(bt_result, methods = c("QP"), sample = "TCGA-AB-3012", signatures = c("Sig1", "Sig2") ) p2 ## Show bootstrap error ## Similar to exposure above p <- show_sig_bootstrap_error(bt_result, methods = c("QP")) p p3 <- show_sig_bootstrap_error(bt_result, methods = c("QP"), sample = "TCGA-AB-2802") p3 ## Show exposure (in)stability p4 <- show_sig_bootstrap_stability(bt_result, methods = c("QP")) p4 p5 <- show_sig_bootstrap_stability(bt_result, methods = c("QP"), measure = "MAE") p5 p6 <- show_sig_bootstrap_stability(bt_result, methods = c("QP"), measure = "AbsDiff") p6 p7 <- show_sig_bootstrap_stability(bt_result, methods = c("QP"), measure = "CV") p7 } else { message("Please install package 'BSgenome.Hsapiens.UCSC.hg19' firstly!") } # }