refactored dm om plots and generated the final layout
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28510471f0
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5bdfd03443
5 changed files with 169 additions and 85 deletions
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@ -40,6 +40,8 @@ dm_om_wf_lf_data <- function(df
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, lf_duet = data.frame()
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, wf_mcsm_lig = data.frame()
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, lf_mcsm_lig = data.frame()
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, wf_mmcsm_lig2 = data.frame() # NEW
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, lf_mmcsm_lig2 = data.frame() # NEW
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, wf_foldx = data.frame()
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, lf_foldx = data.frame()
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, wf_deepddg = data.frame()
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@ -638,52 +640,48 @@ table(lf_mcsm_lig$param_type); colnames(lf_mcsm_lig)
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wf_lf_dataL[['wf_mcsm_lig']] = wf_mcsm_lig
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wf_lf_dataL[['lf_mcsm_lig']] = lf_mcsm_lig
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#====================
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# mcsm-NA affinity
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#=========================
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# mmCSM-lig2:
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# data filtered by cut off
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#====================
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if (tolower(gene)%in%geneL_na){
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#---------------
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# mCSM-NA: WF and lF
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#-----------------
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# WF data: mcsm-na
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cols_to_select_mcsm_na = c(static_cols_start, c("mcsm_na_outcome", mcsm_na_dn), static_cols_end)
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#wf_mcsm_na = comb_df_sl[, cols_to_select_mcsm_na]
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wf_mcsm_na = comb_df_sl_na[, cols_to_select_mcsm_na]
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pivot_cols_mcsm_na = cols_to_select_mcsm_na[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_na
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expected_rows_lf = nrow(wf_mcsm_na) * (length(wf_mcsm_na) - length(pivot_cols_mcsm_na))
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expected_rows_lf
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# LF data: mcsm-na
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lf_mcsm_na = gather(wf_mcsm_na
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, key = param_type
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, value = param_value
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, all_of(mcsm_na_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_mcsm_na) == expected_rows_lf){
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cat("\nPASS: long format data created for ", mcsm_na_dn)
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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# NEW columns [outcome and outcome colname]
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lf_mcsm_na$outcome_colname = "mcsm_na_outcome"
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lf_mcsm_na$outcome = lf_mcsm_na$mcsm_na_outcome
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# DROP static cols
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lf_mcsm_na = lf_mcsm_na[!lf_mcsm_na$param_type%in%c(static_cols_end),]
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lf_mcsm_na$param_type = factor(lf_mcsm_na$param_type)
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table(lf_mcsm_na$param_type); colnames(lf_mcsm_na)
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# Assign them to the output list
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wf_lf_dataL[['wf_mcsm_na']] = wf_mcsm_na
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wf_lf_dataL[['lf_mcsm_na']] = lf_mcsm_na
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#=========================
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#---------------------
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# mmCSM-lig2: WF and lF
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#----------------------
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# WF data: mmcsm_lig2
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cols_to_select_mmcsm_lig2 = c(static_cols_start, c("mmcsm_lig_outcome", mmcsm_lig_dn2), static_cols_end)
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wf_mmcsm_lig2 = comb_df_sl_lig[, cols_to_select_mmcsm_lig2] # filtered df
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pivot_cols_mmcsm_lig2 = cols_to_select_mmcsm_lig2[1: (length(static_cols_start) + 1)]; pivot_cols_mmcsm_lig2
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expected_rows_lf = nrow(wf_mmcsm_lig2) * (length(wf_mmcsm_lig2) - length(pivot_cols_mmcsm_lig2))
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expected_rows_lf
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# LF data: mmcsm_lig2
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lf_mmcsm_lig2 = gather(wf_mmcsm_lig2
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, key = param_type
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, value = param_value
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, all_of(mmcsm_lig_dn2):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_mmcsm_lig2) == expected_rows_lf){
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cat("\nPASS: long format data created for ", mmcsm_lig_dn2)
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}else{
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cat("\nFAIL: long format data could not be created for mmcsm_lig2")
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quit()
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}
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# NEW columns [outcome and outcome colname]
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lf_mmcsm_lig2$outcome_colname = "mmcsm_lig_outcome"
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lf_mmcsm_lig2$outcome = lf_mmcsm_lig2$mmcsm_lig_outcome
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# DROP static cols
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lf_mmcsm_lig2 = lf_mmcsm_lig2[!lf_mmcsm_lig2$param_type%in%c(static_cols_end),]
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lf_mmcsm_lig2$param_type = factor(lf_mmcsm_lig2$param_type)
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table(lf_mmcsm_lig2$param_type); colnames(lf_mmcsm_lig2)
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# Assign them to the output list
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wf_lf_dataL[['wf_mmcsm_lig2']] = wf_mmcsm_lig2
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wf_lf_dataL[['lf_mmcsm_lig2']] = lf_mmcsm_lig2
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#=========================
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# mcsm-ppi2 affinity
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# data filtered by cut off
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@ -730,6 +728,54 @@ if (tolower(gene)%in%geneL_ppi2){
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}
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#====================
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# mcsm-NA affinity
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# data filtered by cut off
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#====================
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if (tolower(gene)%in%geneL_na){
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#---------------
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# mCSM-NA: WF and lF
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#-----------------
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# WF data: mcsm-na
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cols_to_select_mcsm_na = c(static_cols_start, c("mcsm_na_outcome", mcsm_na_dn), static_cols_end)
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#wf_mcsm_na = comb_df_sl[, cols_to_select_mcsm_na]
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wf_mcsm_na = comb_df_sl_na[, cols_to_select_mcsm_na]
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pivot_cols_mcsm_na = cols_to_select_mcsm_na[1: (length(static_cols_start) + 1)]; pivot_cols_mcsm_na
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expected_rows_lf = nrow(wf_mcsm_na) * (length(wf_mcsm_na) - length(pivot_cols_mcsm_na))
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expected_rows_lf
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# LF data: mcsm-na
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lf_mcsm_na = gather(wf_mcsm_na
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, key = param_type
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, value = param_value
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, all_of(mcsm_na_dn):tail(static_cols_end,1)
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, factor_key = TRUE)
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if (nrow(lf_mcsm_na) == expected_rows_lf){
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cat("\nPASS: long format data created for ", mcsm_na_dn)
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}else{
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cat("\nFAIL: long format data could not be created for duet")
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quit()
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}
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# NEW columns [outcome and outcome colname]
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lf_mcsm_na$outcome_colname = "mcsm_na_outcome"
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lf_mcsm_na$outcome = lf_mcsm_na$mcsm_na_outcome
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# DROP static cols
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lf_mcsm_na = lf_mcsm_na[!lf_mcsm_na$param_type%in%c(static_cols_end),]
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lf_mcsm_na$param_type = factor(lf_mcsm_na$param_type)
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table(lf_mcsm_na$param_type); colnames(lf_mcsm_na)
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# Assign them to the output list
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wf_lf_dataL[['wf_mcsm_na']] = wf_mcsm_na
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wf_lf_dataL[['lf_mcsm_na']] = lf_mcsm_na
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}
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return(wf_lf_dataL)
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}
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############################################################################
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@ -18,8 +18,9 @@ lf_bp2 <- function(lf_df #lf_duet
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, y_scales = "free_y"
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, colour_bp_strip = "khaki2"
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, dot_size = 3
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, dot_transparency = 1 #0.3: lighter
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, dot_transparency = 0.3 #0.3: lighter
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, violin_quantiles = c(0.25, 0.5, 0.75) # can be NULL
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, line_thickness = 0.65
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, my_ats = 22 # axis text size
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, my_als = 20 # axis label size
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, my_fls = 20 # facet label size
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@ -69,6 +70,7 @@ lf_bp2 <- function(lf_df #lf_duet
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ggplot2::scale_color_manual(values = lf_bp_colours) +
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geom_violin(trim = T
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, size = line_thickness
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, scale = "width"
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, colour = "black"
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#, position = position_dodge(width = 0.9)
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@ -98,11 +100,11 @@ lf_bp2 <- function(lf_df #lf_duet
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, x = ""
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, y = "") +
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stat_compare_means(comparisons = my_comparisonsL
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, method = stat_method
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, paired = my_paired
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, label = stat_label[2]) +
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, label = stat_label[2]
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, size = 5) +
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geom_quasirandom(
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size = dot_size
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, alpha = dot_transparency
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