various usability tweaks to LogoPlotMSA and position_annotation
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4 changed files with 197 additions and 130 deletions
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@ -124,7 +124,7 @@ install.packages("data.table")
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if (!require("PerformanceAnalytics")){
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install.packages("PerformanceAnalytics", dependencies = T)
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library(PerformaceAnalytics)
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library(PerformanceAnalytics)
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}
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if (!require ("GGally")){
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@ -134,7 +134,7 @@ if(!require("data.table")) {
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if (!require("PerformanceAnalytics")){
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install.packages("PerformanceAnalytics", dependencies = T)
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library(PerformaceAnalytics)
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library(PerformanceAnalytics)
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}
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if (!require ("GGally")){
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@ -40,35 +40,40 @@
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###########################################
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#LogoPlotMSA <- function(msaSeq_mut # chr vector
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# , msaSeq_wt # chr vector
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LogoPlotMSA <- function(unified_msa
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LogoPlotMSA <- function(# unified_msa # <- not needed any more because we have 'target' now
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target = 'embb'
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, logo_type = c("EDLogo") #"bits_pfm", "probability_pfm", "bits_raw", "probability_raw")
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, EDScore_type = c("log") # see if this relevant, or source function should have it!
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, bg_prob = NULL
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, my_logo_col = "chemistry"
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, plot_positions
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, y_breaks
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, x_lab_mut = "nsSNP position"
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, x_lab_mut = ""
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, y_lab_mut
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, x_ats = 13 # text size
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, x_ats = 10 # text size
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, x_tangle = 90 # text angle
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, x_axis_offset = 0 # dist b/w y-axis and plot start
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, x_axis_offset_filtered = 0
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, y_axis_offset = 0
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, y_axis_increment = 1
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, y_ats = 13
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, y_ats = 10
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, y_tangle = 0
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, x_tts = 13 # title size
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, y_tts = 13
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, x_tts = 10 # title size
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, y_tts = 10
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, leg_pos = "top" # can be top, left, right and bottom or c(0.8, 0.9)
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, leg_dir = "horizontal" #can be vertical or horizontal
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, leg_ts = 16 # leg text size
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, leg_tts = 16 # leg title size
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, leg_ts = 14 # leg text size
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, leg_tts = 14 # leg title size
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, ...
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)
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{
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# FIXME: Hack!
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# msaSeq_mut=unified_msa[[1]]
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# msaSeq_wt=unified_msa[[2]]
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unified_msa = get(paste0(target, "_unified_msa"))
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msaSeq_mut=unified_msa[['msa_seq']]
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msaSeq_wt=unified_msa[['wt_seq']]
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@ -79,6 +84,51 @@ LogoPlotMSA <- function(unified_msa
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names(data_ed)
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#"pfm_mutM" "pfm_mut_scaledM" "combED_mutM" "pfm_wtM" "pfm_wt_scaledM" "combED_wtM"
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#merged_df3 for current target (unfortunatly i can't think of an easy way to get this from unified_msa)
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contig_df=data.frame(position=1:max(nchar(unified_msa$wt_seq)))
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plot_df = get(paste0(target, "_merged_df3"))
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# generate the tile columns
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#plot_df=cbind(embb_merged_df3)
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plot_df$col_aa = ifelse(plot_df[["position"]]%in%active_aa_pos,
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"transparent", "transparent")
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plot_df$bg_all = plot_df$col_aa
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plot_df$bg_all = ifelse(plot_df[["position"]]%in%aa_pos_drug,
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"drug", plot_df$bg_all)
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plot_df$col_bg1 = plot_df$bg_all
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plot_df$col_bg1 = ifelse(plot_df[["position"]]%in%aa_pos_lig1,
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"lig1", plot_df$col_bg1)
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plot_df$col_bg2 = plot_df$col_bg1
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plot_df$col_bg2 = ifelse(plot_df[["position"]]%in%aa_pos_lig2,
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"lig2", plot_df$col_bg2)
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plot_df$col_bg3 = plot_df$col_bg2
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plot_df$col_bg3 = ifelse(plot_df[["position"]]%in%aa_pos_lig3
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, "lig3", plot_df$col_bg3)
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plot_df = generate_distance_colour_map(plot_df, debug=FALSE)
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# copy only the tile columns to the contiguous DF
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contig_df$ligand_distance = plot_df$ligand_distance[match(contig_df$position, plot_df$position)]
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contig_df_map = generate_distance_colour_map(contig_df, debug=TRUE)
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contig_df$ligD_colours = contig_df_map$ligD_colours[match(contig_df$position, contig_df_map$position)]
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#contig_df$ligD_colours = plot_df$ligD_colours[match(contig_df$position, plot_df$position)]
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contig_df$bg_all = plot_df$bg_all[match(contig_df$position, plot_df$position)]
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contig_df$col_bg1 = plot_df$col_bg1[match(contig_df$position, plot_df$position)]
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contig_df$col_bg2 = plot_df$col_bg2[match(contig_df$position, plot_df$position)]
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contig_df$col_bg3 = plot_df$col_bg3[match(contig_df$position, plot_df$position)]
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contig_df=replace_na(
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contig_df,
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list(
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ligD_colours='transparent',
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bg_all = 'transparent',
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col_bg1 = 'transparent',
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col_bg2 = 'transparent',
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col_bg3 = 'transparent'
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)
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)
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if (logo_type == "EDLogo"){
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msa_method = "custom"
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y_label = "Enrichment Score"
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@ -416,7 +466,7 @@ LogoPlotMSA <- function(unified_msa
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) +
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scale_y_discrete(expand = c(0,0)) +
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ylab("") + xlab("Wild-type position")
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ylab("") + xlab("")
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if (missing(plot_positions)){
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@ -430,13 +480,27 @@ LogoPlotMSA <- function(unified_msa
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#labels = i_extract,
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limits = factor(i_extract)
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)
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#plot_df=plot_df[plot_df$position %in% plot_positions,]
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contig_df=contig_df[contig_df$position %in% plot_positions,]
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anno_bar = position_annotation(
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contig_df,
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aa_pos_drug=aa_pos_drug,
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active_aa_pos=active_aa_pos,
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aa_pos_lig1=aa_pos_lig1,
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aa_pos_lig2=aa_pos_lig2,
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aa_pos_lig3=aa_pos_lig3,
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generate_colours = FALSE
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)
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}
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cowplot::plot_grid(ed_mut_logo_P
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, ed_wt_logo_P
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, nrow = 2
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, anno_bar
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, ncol = 1
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, align = "v"
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#, axis='lr'
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, rel_heights = c(3/4, 1/4))
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, rel_heights = c(3/4, 1/4,1/10))
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}
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#LogoPlotMSA(unified_msa)
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@ -4,6 +4,7 @@
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position_annotation=function(plot_df,
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bg="transparent",
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reorder_position = FALSE, # enable to reorder according to plot_df$pos_count
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generate_colours = TRUE, #set FALSE if you want to generate all the colour columns elsewhere
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aa_pos_drug=1:100,
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active_aa_pos=1:100,
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aa_pos_lig1=1:100,
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@ -32,6 +33,8 @@ position_annotation=function(plot_df,
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#plot_df = generate_distance_colour_map(plot_df, debug=TRUE)
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# plot_df$col_aa = ifelse(plot_df[["position"]]%in%active_aa_pos,
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# "brown", "transparent")
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if (generate_colours){
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plot_df$col_aa = ifelse(plot_df[["position"]]%in%active_aa_pos,
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"transparent", "transparent")
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@ -55,7 +58,7 @@ position_annotation=function(plot_df,
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# the call to generate_distance_colour_map should probably be
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# wherever the outer DF is built, and not here.
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plot_df = generate_distance_colour_map(plot_df, debug=TRUE)
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}
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heat_bar = ggplot(plot_df) + # THIS STUPID FUCKING FACTOR THING
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# scale_x_discrete("Position", labels=factor(plot_df$position)) +
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