Author: Alan O’Callaghan (alan.b.ocallaghan@gmail.com)
This vignette illustrates the clustering of non-centered breast cancer RNAseq data, similar to the centered data. shown in the main biological data vignette in this package.
pam50_genes <- intersect(pam50_genes, rownames(raw_expression))
raw_pam50_expression <- raw_expression[pam50_genes, ]
voomed_pam50_expression <- voomed_expression[pam50_genes, ]
log_raw_mat <- log2(raw_pam50_expression + 0.5)
heatmaply(t(log_raw_mat),
row_side_colors = tcga_brca_clinical,
showticklabels = c(TRUE, FALSE),
fontsize_col = 7.5,
col = gplots::bluered(50),
main = 'Pre-normalisation log2 counts, PAM50 genes',
plot_method = 'plotly')heatmaply_cor(cor(log_raw_mat),
row_side_colors = tcga_brca_clinical,
showticklabels = c(FALSE, FALSE),
main = 'Sample-sample correlation based on log2-transformed PAM50 gene expression',
plot_method = 'plotly')heatmaply(t(voomed_pam50_expression),
row_side_colors = tcga_brca_clinical,
showticklabels = c(TRUE, FALSE),
fontsize_col = 7.5,
col = gplots::bluered(50),
main = 'Normalised log2 CPM, PAM50 genes',
plot_method = 'plotly')heatmaply_cor(cor(voomed_pam50_expression),
row_side_colors = tcga_brca_clinical,
showticklabels = c(FALSE, FALSE),
main = 'Sample-sample correlation based on normalised PAM50 gene expression',
plot_method = 'plotly')sessionInfo()#> R version 3.4.1 (2017-06-30)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 7 x64 (build 7601) Service Pack 1
#>
#> Matrix products: default
#>
#> locale:
#> [1] LC_COLLATE=Hebrew_Israel.1255 LC_CTYPE=Hebrew_Israel.1255
#> [3] LC_MONETARY=Hebrew_Israel.1255 LC_NUMERIC=C
#> [5] LC_TIME=Hebrew_Israel.1255
#>
#> attached base packages:
#> [1] parallel stats graphics grDevices datasets utils methods
#> [8] base
#>
#> other attached packages:
#> [1] gplots_3.0.1 limma_3.22.7
#> [3] ALL_1.7.1 Biobase_2.26.0
#> [5] BiocGenerics_0.12.1 dendextend_1.6.0
#> [7] glmnet_2.0-10 foreach_1.4.3
#> [9] Matrix_1.2-10 bindrcpp_0.2
#> [11] knitr_1.16 heatmaplyExamples_0.1.0
#> [13] heatmaply_0.11.0 viridis_0.4.0
#> [15] viridisLite_0.2.0 plotly_4.7.1
#> [17] ggplot2_2.2.1.9000 installr_0.19.0
#> [19] stringr_1.2.0
#>
#> loaded via a namespace (and not attached):
#> [1] httr_1.2.1 tidyr_0.6.3 jsonlite_1.5
#> [4] gtools_3.5.0 shiny_1.0.3 assertthat_0.2.0
#> [7] stats4_3.4.1 yaml_2.1.14 robustbase_0.92-7
#> [10] backports_1.1.0 lattice_0.20-35 glue_1.1.1
#> [13] digest_0.6.12 RColorBrewer_1.1-2 colorspace_1.3-2
#> [16] httpuv_1.3.5 htmltools_0.3.6 plyr_1.8.4
#> [19] devtools_1.13.2 pkgconfig_2.0.1 xtable_1.8-2
#> [22] purrr_0.2.2.2 mvtnorm_1.0-6 scales_0.5.0
#> [25] gdata_2.18.0 whisker_0.3-2 tibble_1.3.4
#> [28] mgcv_1.8-17 withr_2.0.0 nnet_7.3-12
#> [31] lazyeval_0.2.0 mime_0.5 magrittr_1.5
#> [34] mclust_5.3 memoise_1.1.0 evaluate_0.10.1
#> [37] nlme_3.1-131 MASS_7.3-47 class_7.3-14
#> [40] tools_3.4.1 registry_0.3 data.table_1.10.4
#> [43] trimcluster_0.1-2 kernlab_0.9-25 munsell_0.4.3
#> [46] cluster_2.0.6 fpc_2.1-10 compiler_3.4.1
#> [49] caTools_1.17.1 rlang_0.1.2 grid_3.4.1
#> [52] iterators_1.0.8 htmlwidgets_0.9 crosstalk_1.0.0
#> [55] labeling_0.3 bitops_1.0-6 rmarkdown_1.6
#> [58] gtable_0.2.0 codetools_0.2-15 flexmix_2.3-14
#> [61] reshape2_1.4.2 TSP_1.1-5 R6_2.2.2
#> [64] seriation_1.2-2 gridExtra_2.2.1 prabclus_2.2-6
#> [67] dplyr_0.7.3.9000 bindr_0.1 rprojroot_1.2
#> [70] KernSmooth_2.23-15 modeltools_0.2-21 stringi_1.1.5
#> [73] Rcpp_0.12.12 gclus_1.3.1 DEoptimR_1.0-8
#> [76] diptest_0.75-7