Analysis of TCGA RPPA LIHC samples
Jovan Tanevski
2021-07-28
Last updated: 2021-07-28
Checks: 7 0
Knit directory: Multispectral HCC/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 9ab4acc | Jovan Tanevski | 2021-07-28 | Build site. |
| Rmd | bd05dbf | Jovan Tanevski | 2021-07-28 | add expression profiles |
| html | e45bf1d | Jovan Tanevski | 2021-07-28 | Build site. |
| Rmd | dcab1bf | Jovan Tanevski | 2021-07-28 | set figure output to svg |
| html | 33e71a0 | Jovan Tanevski | 2021-07-28 | Build site. |
| Rmd | bb998b8 | Jovan Tanevski | 2021-07-28 | hclust with factoextra |
| html | 1cb80af | Jovan Tanevski | 2021-07-28 | Build site. |
| Rmd | d0b6e0f | Jovan Tanevski | 2021-07-28 | add pca to tcga analysis |
| html | d73f586 | Jovan Tanevski | 2021-07-28 | Build site. |
| Rmd | c4324f5 | Jovan Tanevski | 2021-07-28 | add umap |
| html | 0bfae68 | Jovan Tanevski | 2021-07-28 | Build site. |
| Rmd | 82e3712 | Jovan Tanevski | 2021-07-28 | add basic hclust |
Setup
Load required libraries.
library(tidyverse)
library(skimr)
library(uwot)
library(factoextra)
library(cowplot)Read filtered TCGA RRPA data and display summary statistics.
tcga <- read_csv("data/TCGA-RPPA-LIHC_selected.csv", col_types = cols()) %>%
select(-TumorType) %>%
column_to_rownames("SampleID")
skim(tcga)| Name | tcga |
| Number of rows | 184 |
| Number of columns | 12 |
| _______________________ | |
| Column type frequency: | |
| numeric | 12 |
| ________________________ | |
| Group variables | None |
Variable type: numeric
| skim_variable | n_missing | complete_rate | mean | sd | p0 | p25 | p50 | p75 | p100 | hist |
|---|---|---|---|---|---|---|---|---|---|---|
| P53 | 0 | 1 | -1.13 | 0.46 | -2.54 | -1.40 | -0.96 | -0.76 | -0.51 | ▁▂▂▅▇ |
| AKT_pS473 | 0 | 1 | -0.63 | 0.71 | -2.76 | -1.02 | -0.41 | -0.15 | 0.96 | ▁▂▃▇▁ |
| AKT_pT308 | 0 | 1 | 0.07 | 0.42 | -1.16 | -0.07 | 0.09 | 0.22 | 1.72 | ▁▃▇▁▁ |
| BETACATENIN | 0 | 1 | 1.50 | 0.72 | -1.30 | 1.08 | 1.51 | 1.87 | 3.70 | ▁▁▇▅▁ |
| JNK_pT183Y185 | 0 | 1 | -0.21 | 0.29 | -1.14 | -0.36 | -0.17 | -0.04 | 0.48 | ▁▂▇▇▂ |
| MEK1_pS217S221 | 0 | 1 | -0.17 | 0.36 | -0.82 | -0.35 | -0.23 | -0.10 | 2.58 | ▇▃▁▁▁ |
| P38_pT180Y182 | 0 | 1 | 0.49 | 0.57 | -1.45 | 0.31 | 0.50 | 0.72 | 2.95 | ▁▂▇▁▁ |
| P70S6K_pT389 | 0 | 1 | -1.21 | 0.75 | -3.22 | -1.58 | -0.95 | -0.65 | 1.09 | ▂▃▇▃▁ |
| PDK1_pS241 | 0 | 1 | 0.40 | 0.31 | -0.56 | 0.23 | 0.37 | 0.55 | 1.62 | ▁▇▇▂▁ |
| S6_pS235S236 | 0 | 1 | -0.72 | 0.75 | -3.53 | -1.06 | -0.67 | -0.36 | 1.12 | ▁▁▅▇▂ |
| YAP_pS127 | 0 | 1 | 2.21 | 0.61 | 0.68 | 1.78 | 2.10 | 2.54 | 4.05 | ▁▇▇▂▁ |
| TRANSGLUTAMINASE | 0 | 1 | -0.42 | 0.56 | -1.24 | -0.83 | -0.59 | -0.20 | 2.72 | ▇▃▁▁▁ |
Unsupervised analysis
Perform hierarchical clustering of the data and plot the resulting dendrogram
tcga.hclust <- eclust(tcga, "hclust", k = 4)Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
"none")` instead.fviz_dend(tcga.hclust, rect = TRUE)Warning: `guides(<scale> = FALSE)` is deprecated. Please use `guides(<scale> =
"none")` instead.
| Version | Author | Date |
|---|---|---|
| e45bf1d | Jovan Tanevski | 2021-07-28 |
fviz_silhouette(tcga.hclust) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)) cluster size ave.sil.width
1 1 72 0.05
2 2 15 0.23
3 3 29 -0.04
4 4 68 0.25
| Version | Author | Date |
|---|---|---|
| e45bf1d | Jovan Tanevski | 2021-07-28 |
Project to 2D with PCA and UMAP and plot
tcga.pca <- prcomp(tcga)
summary(tcga.pca)Importance of components:
PC1 PC2 PC3 PC4 PC5 PC6 PC7
Standard deviation 1.2123 0.8248 0.6607 0.56514 0.52805 0.47568 0.43431
Proportion of Variance 0.3831 0.1773 0.1138 0.08325 0.07268 0.05898 0.04917
Cumulative Proportion 0.3831 0.5604 0.6742 0.75746 0.83014 0.88912 0.93829
PC8 PC9 PC10 PC11 PC12
Standard deviation 0.31055 0.24392 0.2216 0.14622 0.10156
Proportion of Variance 0.02514 0.01551 0.0128 0.00557 0.00269
Cumulative Proportion 0.96343 0.97894 0.9917 0.99731 1.00000fviz_pca_biplot(tcga.pca, label = "var", col.ind = as.factor(tcga.hclust$cluster)) +
theme_classic()
| Version | Author | Date |
|---|---|---|
| e45bf1d | Jovan Tanevski | 2021-07-28 |
tcga.umap <- umap(tcga, n_neighbors = 5, n_epochs = 1000) %>%
cbind(tcga.hclust$cluster) %>%
`colnames<-`(c("U1", "U2", "Cluster")) %>%
as_tibble() %>%
mutate_at("Cluster", as.factor)
ggplot(tcga.umap, aes(x = U1, y = U2, color = Cluster, shape = Cluster)) +
geom_point() +
theme_classic()
| Version | Author | Date |
|---|---|---|
| e45bf1d | Jovan Tanevski | 2021-07-28 |
Expression profiles per cluster
tcga.clustered <- tcga %>%
mutate(Cluster = as.factor(tcga.hclust$cluster)) %>%
pivot_longer(names_to = "Marker", values_to = "Z", -Cluster)
profiles <- seq_len(4) %>% map(~
ggplot(
tcga.clustered %>% filter(Cluster == .x),
aes(x = Marker, y = Z, color = Marker)
) +
stat_summary(fun.data = mean_sdl, show.legend = FALSE) +
ylim(-3, 3) +
theme_classic() +
theme(axis.text.x = element_text(angle = 90, hjust = 1)))
plot_grid(plotlist = profiles, labels = paste("Cluster", seq_len(4)))Warning: Removed 7 rows containing non-finite values (stat_summary).Warning: Removed 20 rows containing non-finite values (stat_summary).Warning: Removed 3 rows containing missing values (geom_segment).Warning: Removed 4 rows containing non-finite values (stat_summary).Warning: Removed 2 rows containing missing values (geom_segment).Warning: Removed 2 rows containing non-finite values (stat_summary).
sessionInfo()R version 4.1.0 (2021-05-18)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] cowplot_1.1.1 factoextra_1.0.7 uwot_0.1.10 Matrix_1.3-4
[5] skimr_2.1.3 forcats_0.5.1 stringr_1.4.0 dplyr_1.0.7
[9] purrr_0.3.4 readr_2.0.0 tidyr_1.1.3 tibble_3.1.3
[13] ggplot2_3.3.5 tidyverse_1.3.1 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] colorspace_2.0-2 ggsignif_0.6.2 ellipsis_0.3.2
[4] rio_0.5.27 rprojroot_2.0.2 htmlTable_2.2.1
[7] base64enc_0.1-3 fs_1.5.0 rstudioapi_0.13
[10] ggpubr_0.4.0 farver_2.1.0 ggrepel_0.9.1
[13] bit64_4.0.5 RSpectra_0.16-0 fansi_0.5.0
[16] lubridate_1.7.10 xml2_1.3.2 splines_4.1.0
[19] knitr_1.33 Formula_1.2-4 jsonlite_1.7.2
[22] broom_0.7.8 cluster_2.1.2 dbplyr_2.1.1
[25] png_0.1-7 compiler_4.1.0 httr_1.4.2
[28] backports_1.2.1 assertthat_0.2.1 cli_3.0.1
[31] later_1.2.0 htmltools_0.5.1.1 tools_4.1.0
[34] gtable_0.3.0 glue_1.4.2 Rcpp_1.0.7
[37] carData_3.0-4 cellranger_1.1.0 jquerylib_0.1.4
[40] vctrs_0.3.8 xfun_0.24 openxlsx_4.2.4
[43] rvest_1.0.0 lifecycle_1.0.0 rstatix_0.7.0
[46] dendextend_1.15.1 scales_1.1.1 vroom_1.5.3
[49] hms_1.1.0 promises_1.2.0.1 parallel_4.1.0
[52] RColorBrewer_1.1-2 yaml_2.2.1 curl_4.3.2
[55] gridExtra_2.3 sass_0.4.0 rpart_4.1-15
[58] latticeExtra_0.6-29 stringi_1.7.3 highr_0.9
[61] checkmate_2.0.0 zip_2.2.0 repr_1.1.3
[64] rlang_0.4.11 pkgconfig_2.0.3 evaluate_0.14
[67] lattice_0.20-44 htmlwidgets_1.5.3 labeling_0.4.2
[70] bit_4.0.4 tidyselect_1.1.1 magrittr_2.0.1
[73] R6_2.5.0 generics_0.1.0 Hmisc_4.5-0
[76] DBI_1.1.1 pillar_1.6.1 haven_2.4.1
[79] whisker_0.4 foreign_0.8-81 withr_2.4.2
[82] survival_3.2-11 abind_1.4-5 nnet_7.3-16
[85] modelr_0.1.8 crayon_1.4.1 car_3.0-11
[88] utf8_1.2.2 tzdb_0.1.2 rmarkdown_2.9
[91] viridis_0.6.1 jpeg_0.1-9 grid_4.1.0
[94] readxl_1.3.1 data.table_1.14.0 FNN_1.1.3
[97] git2r_0.28.0 reprex_2.0.0 digest_0.6.27
[100] httpuv_1.6.1 munsell_0.5.0 viridisLite_0.4.0
[103] bslib_0.2.5.1