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Small updates to plots + subtype AUC interaction #71

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Small updates to plots + subtype AUC interaction #71

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6 changes: 6 additions & 0 deletions .gitignore
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Original file line number Diff line number Diff line change
Expand Up @@ -91,3 +91,9 @@ cohort_summary/NMF/multinomial_models_k_4_elastic_net/cell_line_data_notes.txt
cohort_summary/NMF/peptide_subtype_interaction/Protein peptide deviation Vlad.pptx
cohort_summary/NMF/peptide_subtype_interaction/Protein Peptide Deviation PTRC tuesday.pptx
cohort_summary/supplemental_table_1.txt
cohort_summary/NMF/cophenetic_correlation.txt
cohort_summary/NMF/logFC.txt
cohort_summary/NMF/subtype_mutation_AUC/drug_response.csv
cohort_summary/NMF/subtype_mutation_AUC/Figures
Figures
cohort_summary/NMF/diving_into_subtype_drivers.Rmd
2 changes: 1 addition & 1 deletion cohort_summary/NMF/NMF_raw_results.Rmd
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Expand Up @@ -12,12 +12,12 @@ library(dplyr)
library(tibble)
library(tidyr)


source("../../util/synapseUtil.R")
source("../../util/loading_data.R")
source("NMF_helper.R")
load.combined.data()


```


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14 changes: 9 additions & 5 deletions cohort_summary/NMF/NMF_summary.Rmd
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Expand Up @@ -120,6 +120,9 @@ coph.correlation <- sapply(results, cophcor) %>%
data.frame(coph.cor = ., k = 2:8) %>%
filter(k <= 8)

write.table(coph.correlation, file = "cophenetic_correlation.txt",
sep = "\t", quote = F, row.names = F)

p <- ggplot(coph.correlation, aes(x = k, y = coph.cor)) + geom_line() +
ylab("Cophenetic correlation") + scale_x_continuous(breaks = 2:8)

Expand Down Expand Up @@ -229,7 +232,7 @@ fab_annotations <- summary.table %>%
## pheatmap column labels
ann.labels <- meta %>%
filter(Barcode.ID %in% samples.common) %>%
select(FLT3.ITD, PostChemotherapy, vitalStatus) %>%
select(FLT3.ITD, PostChemotherapy) %>%
mutate(FLT3.ITD = as.factor(FLT3.ITD),
PostChemotherapy = as.factor(PostChemotherapy),
Barcode.ID = rownames(.))
Expand Down Expand Up @@ -260,12 +263,12 @@ ann.labels <- ann.labels %>%
mutate(FAB = factor(FAB, levels = c("M0", "M1", "M2", "M3", "M4", "M5", "None"))) %>%
column_to_rownames("Barcode.ID") %>%
as.data.frame() %>%
select(PostChemotherapy, NPM1, NPM1_clinical, RAS, vitalStatus, FLT3.ITD, FLT3_MAF, FLT3_AR, FAB) %>%
select(PostChemotherapy, NPM1, NPM1_clinical, RAS, FLT3.ITD, FLT3_MAF, FLT3_AR, FAB) %>%
dplyr::rename(`FLT3_MAF (percentage)` = FLT3_MAF,
`RAS vaf` = RAS)

## Slimming down annotations
ann.labels <- ann.labels[, c("RAS vaf", "FLT3.ITD", "NPM1_clinical", "FAB", "vitalStatus")]
ann.labels <- ann.labels[, c("RAS vaf", "FLT3.ITD", "NPM1_clinical", "FAB")] #, "vitalStatus")]

## White to dark purple (like the snow storms on weather maps)
colors.wp <- scales::seq_gradient_pal("#FFFFFF", "#4A0078", "Lab")(seq(0,1,length.out = p.celing*10 + 1))
Expand All @@ -282,9 +285,10 @@ ann.colors <- lapply(names(ann.labels), function(x){
"None" = "white")
} else if (length(levels(ann.labels[[x]])) == 2) {
c(`FALSE` = "white", `TRUE` = "darkgrey")
} else {
c("Alive" = "white", "Dead" = "darkgrey", "Unknown" = "brown")
}
# } else {
# c("Alive" = "white", "Dead" = "darkgrey", "Unknown" = "brown")
# }
})
names(ann.colors) <- names(ann.labels)

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14 changes: 7 additions & 7 deletions ...ry/NMF/multinomial_models_k_4_elastic_net/k_4_enet_multinomial_predictions_cell_lines.Rmd
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Expand Up @@ -269,6 +269,7 @@ combined <- get_probabilities(tram$`Global msnset`, tram_comp$`Global msnset`) %


```{r Quizartinib Resistance setup}
##Updating for paper

## Quizartinib Resistance Proteomics Data
quizProtData <- querySynapseTable('syn23595222') %>%
Expand Down Expand Up @@ -621,6 +622,7 @@ ggsave(plot = p, filename = path_str, height = 5, width = 7)


```{r Quizartinib Resistance}
##Updating for paper
m <- quiz$`Global msnset`
plot_title <- "Quizartinib Resistance"
path_str <- tolower(plot_title) %>% gsub(" ", "_", .)
Expand Down Expand Up @@ -680,10 +682,9 @@ alluvial_df <- quiz_meta %>%
p3 <- ggplot(alluvial_df,
aes(x = CellLine, y = Proportion, alluvium = Subtype)) +
geom_alluvium(aes(fill = Subtype)) + scale_fill_manual(values = subtype_colors) +
scale_x_discrete(expand = c(0.15, 0)) +
ggtitle(plot_title) + scale_x_discrete(expand = c(0.3, 0)) +
ggtitle(plot_title) +
theme(axis.title.x = element_blank(),
axis.text.x = element_text(size = 7))
axis.text.x = element_text(size = 9, angle = 45, vjust = .65))

path_str <- sub(".pdf$", "_no_ligand.pdf", path_str)
ggsave(plot = p3, filename = path_str, height = 5.2, width = 10)
Expand All @@ -708,13 +709,12 @@ alluvial_df <- quiz_meta %>%
p4 <- ggplot(alluvial_df,
aes(x = CellLine, y = Proportion, alluvium = Subtype)) +
geom_alluvium(aes(fill = Subtype)) + scale_fill_manual(values = subtype_colors) +
scale_x_discrete(expand = c(0.3, 0)) +
ggtitle(plot_title) + scale_x_discrete(expand = c(0.3, 0)) +
ggtitle(plot_title) +
theme(axis.title.x = element_blank(),
axis.text.x = element_text(size = 7))
axis.text.x = element_text(size = 9, angle = 45, vjust = .65))

path_str <- sub(".pdf$", "_v2.pdf", path_str)
ggsave(plot = p4, filename = path_str, height = 5.2, width = 7)
ggsave(plot = p4, filename = path_str, height = 5.2, width = 8)


```
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13 changes: 13 additions & 0 deletions ...summary/NMF/multinomial_models_k_4_elastic_net/k_4_enet_multinomial_predictions_pilot.Rmd
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Expand Up @@ -275,6 +275,19 @@ drug_data <- auc.dat %>%

```


```{r}
table_df <- pilot_meta %>%
filter(exp_3_new) %>%
select(Sample = sample, Subtype, `New to 210-patient cohort` = exp_3_new)
write.table(table_df, "enet_multinomial_data/experiment_3_new_samples.txt", sep = "\t",
col.names = TRUE, row.names = FALSE, quote = F)


```



```{r}
cohort_subtypes <- read.table(syn$get("syn30030154")$path) %>%
dplyr::rename(Subtype = Cluster) %>%
Expand Down
8 changes: 5 additions & 3 deletions cohort_summary/NMF/subtype_drivers.Rmd
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Expand Up @@ -176,9 +176,10 @@ ksea_wrap <- function(m, var_name, top_n = 7, font_size = 7, ending = "", ...){
plot_path <- paste0("Data/subtype_drivers/ksea_", var_name, ".pdf")
}

colnames(ksea_mat) <- sub("^Cluster", "Subtype", colnames(ksea_mat))
heatmap_breaks <- seq(-5, 5, by = 0.2)
heatmap_colors <- colorRampPalette(rev(brewer.pal(n = 7, name = "RdYlBu")))(length(heatmap_breaks))
p <- pheatmap(ksea_mat, display_numbers = ksea_mat_p2, cluster_cols = F, fontsize = 9,
p <- pheatmap(ksea_mat, display_numbers = ksea_mat_p2, cluster_cols = F, fontsize = 9, fontsize_number = 15,
fontsize_row = font_size, main = title, treeheight_row = 0, cellwidth = 33,
breaks = heatmap_breaks, color = heatmap_colors, width = 6,
filename = plot_path, ...)
Expand Down Expand Up @@ -274,10 +275,11 @@ rank_gsea <- function(m, var_name, t2g, wrap_width = 40, font_size = 7,
plot_path <- paste0("Data/subtype_drivers/rank_gsea_", var_name, ".pdf")
}

p <- pheatmap(gsea_mat, display_numbers = gsea_mat_p2, cluster_cols = F, fontsize = 9,
colnames(gsea_mat) <- sub("^Cluster", "Subtype", colnames(gsea_mat))
p <- pheatmap(gsea_mat, display_numbers = gsea_mat_p2, cluster_cols = F, fontsize = 9, fontsize_number = 15,
fontsize_row = font_size, main = title, treeheight_row = 0, cellwidth = 33,
width = 6, filename = plot_path, ...)
pheatmap(gsea_mat, display_numbers = gsea_mat_p2, cluster_cols = F, fontsize = 9,
pheatmap(gsea_mat, display_numbers = gsea_mat_p2, cluster_cols = F, fontsize = 9, fontsize_number = 15,
fontsize_row = font_size, main = title, treeheight_row = 0, cellwidth = 33,
width = 6, filename = sub(".pdf$", ".png", plot_path), ...)

Expand Down
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