--- a
+++ b/R/Data_Source_Comparison.R
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+# Find the percentage of cell lines with proteomics data that also have drug response data in DepMap
+
+require(data.table)
+d <- fread("/Users/ftaj/Downloads/primary-screen-replicate-collapsed-logfold-change.csv")
+protein <- fread("/Users/ftaj/OneDrive - University of Toronto/Drug_Response/Data/DepMap/20Q2/CCLE_protein_quant_current_normalized.csv")
+cells <- fread("/Users/ftaj/OneDrive - University of Toronto/Drug_Response/Data/DepMap/20Q2/DepMap_Cell_Line_info-3.csv")
+
+dim(d)
+
+c <- c[, c("DepMap_ID", "CCLE_Name")]
+cp <- merge(c, p, by.x = "CCLE_Name", by.y = "CCLE Code")
+p
+ 
+sum(cp$DepMap_ID %in% d$V1)/375
+colnames(d)
+
+
+# ==== Compare to GDSC ====
+require(data.table)
+gdsc1 <- fread("/Users/ftaj/OneDrive - University of Toronto/Drug_Response/Data/GDSC/GDSC1_Fitted_Dose_Response.csv")
+length(unique(gdsc1$CELL_LINE_NAME))  # 987 cell lines in GDSC2
+gdsc2 <- fread("/Users/ftaj/OneDrive - University of Toronto/Drug_Response/Data/GDSC/GDSC2_Fitted_Dose_Response.csv")
+length(unique(gdsc2$CELL_LINE_NAME))  # 809 cell lines in GDSC2
+
+gdsc_cells <- fread("/Users/ftaj/OneDrive - University of Toronto/Drug_Response/Data/GDSC/GDSC_Cell_Lines_Details.csv")
+
+# Find overlap with DepMap cell lines
+sum(toupper(gdsc_cells$`Sample Name`) %in% toupper(cells$stripped_cell_line_name)) / length(gdsc_cells$`Sample Name`)
+sum(toupper(gdsc_cells$`COSMIC identifier`) %in% toupper(cells$COSMICID)) / length(gdsc_cells$`Sample Name`)
+# COSMIC IDs have ~98% overlap
+# This implies that different names are being used
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