renamed logoP_msa.R --> logoP_msa_raw.R
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4 changed files with 316 additions and 267 deletions
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@ -1,39 +1,14 @@
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library(Logolas)
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library(ggseqlogo)
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source("~/git/LSHTM_analysis/scripts/functions/my_logolas.R")
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# data msa: mut
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my_data = read.csv("/home/tanu/git/Misc/practice_plots/pnca_msa_eg2.csv", header = F) #15 cols only
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msaSeq_mut = my_data$V1
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# data msa: wt
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gene = "pncA"
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drug = "pyrazinamide"
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indir = paste0("~/git/Data/", drug , "/input/")
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in_filename_fasta = paste0(tolower(gene), "2_f2.fasta")
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infile_fasta = paste0(indir, in_filename_fasta)
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cat("\nInput fasta file for WT: ", infile_fasta, "\n")
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msa2 = read.csv(infile_fasta, header = F)
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head(msa2)
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cat("\nLength of WT fasta:", nrow(msa2))
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#wt_seq = msa2$V1
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#head(wt_seq)
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msaSeq_wt = msa2$V1
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###########################################
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PlotLogolasMSA <- function(msaSeq_mut # chr vector
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, msaSeq_wt # chr vector
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, msa_method = c("custom") # will be c("EDLogo", "Logo)#
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, EDLogo_score = c("log")# can be: "log-odds", "diff", "probKL", "ratio", "unscaled_log", "wKL"
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, ED_score = c("log")# can be: "log-odds", "diff", "probKL", "ratio", "unscaled_log", "wKL"
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, bg_prob = NULL
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, my_logo_col = "chemistry"
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, plot_positions = c(1, 10, 14, 8)
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, plot_positions
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, y_breaks
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, x_lab = "Wild-type position"
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, y_lab = ""
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, x_lab_mut = "nsSNP-position"
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, y_lab_mut = ""
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, x_ats = 13 # text size
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, x_tangle = 90 # text angle
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, x_axis_offset = 0.05 # dist b/w y-axis and plot start
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@ -50,6 +25,7 @@ PlotLogolasMSA <- function(msaSeq_mut # chr vector
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)
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{
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#''' Can be put into a separate EDData plot function'''
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dash_control = list()
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dash_control_default <- list(concentration = NULL, mode = NULL,
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optmethod = "mixEM", sample_weights = NULL, verbose = FALSE,
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@ -65,198 +41,206 @@ PlotLogolasMSA <- function(msaSeq_mut # chr vector
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cat("\nLength of MSA", length(msaSeq_mut)
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, "\nlength of WT seq:", length(msaSeq_wt))
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cat("\n======================="
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cat("\n======================="
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, "\nPlotting entire MSA"
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, "\n========================")
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#--------------------------
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# Getting PFM: mutant MSA
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#--------------------------
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pfm_mut <- Biostrings::consensusMatrix(msaSeq_mut)
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colnames(pfm_mut) <- 1:dim(pfm_mut)[2]
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pfm_mut_scaled <- do.call(dash, append(list(comp_data = pfm_mut),
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#--------------------------
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# Getting PFM: mutant MSA
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#--------------------------
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pfm_mut <- Biostrings::consensusMatrix(msaSeq_mut)
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colnames(pfm_mut) <- 1:dim(pfm_mut)[2]
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pfm_mut_scaled <- do.call(dash, append(list(comp_data = pfm_mut),
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dash_control))$posmean
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logo_mut_h = get_logo_heights(pfm_mut_scaled
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, bg = bg_prob
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, score = EDLogo_score)
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logo_mut_h$pos_ic
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logo_mut_h$neg_ic
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logo_mut_h = get_logo_heights(pfm_mut_scaled
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, bg = bg_prob
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, score = ED_score)
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# TODO: Add sanity check!
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#<...
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#...>
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cat("\nGetting logo_heights from Logolas package...")
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pos_mutM = logo_mut_h[['table_mat_pos_norm']]; pos_mutM
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pos_mutS = logo_mut_h$pos_ic; pos_mutS
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pos_mutED = t(pos_mutS*t(pos_mutM)); pos_mutED
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pos_mutM = logo_mut_h[['table_mat_pos_norm']]; pos_mutM
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pos_mutS = logo_mut_h[['pos_ic']]; pos_mutS
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pos_mutED = t(pos_mutS*t(pos_mutM)); pos_mutED
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neg_mutM = logo_mut_h[['table_mat_neg_norm']]*(-1)
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neg_mutS = logo_mut_h$neg_ic; neg_mutS
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neg_mutED = t(neg_mutS*t(neg_mutM)); neg_mutED
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neg_mutM = logo_mut_h[['table_mat_neg_norm']]*(-1)
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neg_mutS = logo_mut_h[['neg_ic']]; neg_mutS
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neg_mutED = t(neg_mutS*t(neg_mutM)); neg_mutED
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combED_mutM = pos_mutED + neg_mutED
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# Construct the x-axis: mutant MSA
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msa_all_pos = as.numeric(colnames(combED_mutM))
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#---------------------
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# Getting PFM: WT
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#---------------------
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pfm_wt <- Biostrings::consensusMatrix(msaSeq_wt)
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colnames(pfm_wt) <- 1:dim(pfm_wt)[2]
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pfm_wt_scaled <- do.call(dash, append(list(comp_data = pfm_wt),
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dash_control))$posmean
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logo_wt_h = get_logo_heights(pfm_wt_scaled
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, bg = bg_prob
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, score = EDLogo_score)
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logo_wt_h$pos_ic
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logo_wt_h$neg_ic
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pos_wtM = logo_wt_h[['table_mat_pos_norm']]; pos_wtM
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pos_wtS = logo_wt_h$pos_ic; pos_wtS
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pos_wtED = t(pos_wtS*t(pos_wtM)); pos_wtED
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neg_wtM = logo_wt_h[['table_mat_neg_norm']]*(-1)
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neg_wtS = logo_wt_h$neg_ic; neg_wtS
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neg_wtED = t(neg_wtS*t(neg_wtM)); neg_wtED
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combED_wtM = pos_wtED + neg_wtED
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# Construct the x-axis: mutant MSA
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wt_all_pos = as.numeric(colnames(combED_wtM))
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if(missing(plot_positions)){
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#------------------------------
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# MSA mut: All, no filtering
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#-------------------------------
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cat("\n==========================================="
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, "\nGenerated PFM mut: No filtering"
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, "\n===========================================")
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plot_mut_edM = combED_mutM
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#------------------------------
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# MSA WT: All, no filtering
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#-------------------------------
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cat("\n==========================================="
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, "\nGenerated PFM WT: No filtering"
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, "\n===========================================")
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plot_wt_edM = combED_wtM
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}else{
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#------------------------------
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# PFM mut: Filtered positions
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#-------------------------------
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cat("\n==========================================="
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, "\nGenerating PFM MSA: filtered positions"
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, "\n==========================================="
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, "\nUser specified plotting positions for MSA:"
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, "\nThese are:\n", plot_positions
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, "\nSorting plot positions...")
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plot_positions = sort(plot_positions)
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cat("\nPlotting positions sorted:\n"
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, plot_positions)
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if ( all(plot_positions%in%msa_all_pos) && all(plot_positions%in%wt_all_pos) ){
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cat("\nAll positions within range"
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, "\nFiltering positions as specified..."
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, "\nNo. of positions in plot:", length(plot_positions))
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i_extract = plot_positions
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plot_mut_edM = combED_mutM[, i_extract]
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plot_wt_edM = combED_wtM[, i_extract]
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}else{
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cat("\nNo. of positions selected:", length(plot_positions))
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i_ofr = plot_positions[!plot_positions%in%msa_all_pos]
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cat("\n1 or more plot_positions out of range..."
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, "\nThese are:\n", i_ofr
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, "\nQuitting! Resubmit with correct plot_positions")
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quit()
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}
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}
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# Construct the y-axis: Calculating
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cat("\n-------------------------"
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, "\nConstructing y-axis:"
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, "\nUser did not provide"
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,"\n--------------------------")
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if (missing(y_breaks)){
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ylim_low <- floor(min(combED_mutM)); ylim_low
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if( ylim_low == 0){
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ylim_low = ylim_low
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cat("\nY-axis lower limit:", ylim_low)
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y_rlow = seq(0, ylim_low, length.out = 3); y_rlow
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ylim_up <- ceiling(max(combED_mutM)) + 4; ylim_up
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cat("\nY-axis upper limit:", ylim_up)
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y_rup = seq(0, ylim_up, by = 2); y_rup
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}else{
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ylim_low = ylim_low + (-0.5)
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cat("\nY-axis lower limit is <0:", ylim_low)
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y_rlow = seq(0, ylim_low, length.out = 3); y_rlow
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ylim_up <- ceiling(max(combED_mutM)) + 3; ylim_up
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cat("\nY-axis upper limit:", ylim_up)
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y_rup = seq(0, ylim_up, by = 3); y_rup
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}
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#ylim_scale <- unique(sort(c(y_rlow, y_rup, ylim_up))); ylim_scale
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ylim_scale <- unique(sort(c(y_rlow, y_rup))); ylim_scale
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cat("\nY-axis generated: see below"
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, "\n"
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, ylim_scale)
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}else{
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# Construct the y-axis: User provided
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cat("\n-------------------------"
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, "\nConstructing y-axis:"
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, "\nUser provided"
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,"\n--------------------------")
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ylim_scale = sort(y_breaks)
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ylim_low = min(ylim_scale); ylim_low
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ylim_up = max(ylim_scale); ylim_up
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}
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else {
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}
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######################################
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# Generating plots for muts and wt
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#####################################
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if (my_logo_col %in% c('clustalx','taylor')) {
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cat("\nSelected colour scheme:", my_logo_col
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, "\nUsing black theme\n")
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theme_bgc = "black"
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xfont_bgc = "white"
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yfont_bgc = "white"
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xtt_col = "white"
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ytt_col = "white"
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if (length(pos_mutS) && length(neg_mutS) == dim(pfm_mut)[2]){
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cat("\nPASS: pfm calculated successfully including scaled matrix"
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, "\nDim of pfm matrix:", dim(pfm_mut)[1], dim(pfm_mut)[2])
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}
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if (my_logo_col %in% c('chemistry', 'hydrophobicity')) {
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cat("\nstart of MSA"
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, '\nSelected colour scheme:', my_logo_col
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, "\nUsing grey theme")
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combED_mutM = pos_mutED + neg_mutED
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# Construct the x-axis: mutant MSA
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msa_all_pos = as.numeric(colnames(combED_mutM))
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#---------------------
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# Getting PFM: WT
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#---------------------
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pfm_wt <- Biostrings::consensusMatrix(msaSeq_wt)
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colnames(pfm_wt) <- 1:dim(pfm_wt)[2]
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pfm_wt_scaled <- do.call(dash, append(list(comp_data = pfm_wt),
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dash_control))$posmean
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logo_wt_h = get_logo_heights(pfm_wt_scaled
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, bg = bg_prob
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, score = ED_score)
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pos_wtM = logo_wt_h[['table_mat_pos_norm']]; pos_wtM
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pos_wtS = logo_wt_h[['pos_ic']]; pos_wtS
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pos_wtED = t(pos_wtS*t(pos_wtM)); pos_wtED
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neg_wtM = logo_wt_h[['table_mat_neg_norm']]*(-1)
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neg_wtS = logo_wt_h[['neg_ic']]; neg_wtS
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neg_wtED = t(neg_wtS*t(neg_wtM)); neg_wtED
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if (length(pos_wtS) && length(neg_wtS) == dim(pfm_wt)[2]){
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cat("\nPASS: pfm calculated successfully including scaled matrix"
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, "\nDim of pfm matrix:", dim(pfm_wt)[1], dim(pfm_wt)[2])
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}
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combED_wtM = pos_wtED + neg_wtED
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# Construct the x-axis: mutant MSA
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wt_all_pos = as.numeric(colnames(combED_wtM))
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if(missing(plot_positions)){
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#------------------------------
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# MSA mut: All, no filtering
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#-------------------------------
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cat("\n==========================================="
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, "\nGenerated PFM mut: No filtering"
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, "\n===========================================")
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plot_mut_edM = combED_mutM
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#------------------------------
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# MSA WT: All, no filtering
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#-------------------------------
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cat("\n==========================================="
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, "\nGenerated PFM WT: No filtering"
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, "\n===========================================")
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plot_wt_edM = combED_wtM
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}else{
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#------------------------------
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# PFM mut: Filtered positions
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#-------------------------------
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cat("\n==========================================="
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, "\nGenerating PFM MSA: filtered positions"
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, "\n==========================================="
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, "\nUser specified plotting positions for MSA:"
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, "\nThese are:\n", plot_positions
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, "\nSorting plot positions...")
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plot_positions = sort(plot_positions)
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cat("\nPlotting positions sorted:\n"
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, plot_positions)
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if ( all(plot_positions%in%msa_all_pos) && all(plot_positions%in%wt_all_pos) ){
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cat("\nAll positions within range"
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, "\nFiltering positions as specified..."
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, "\nNo. of positions in plot:", length(plot_positions))
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i_extract = plot_positions
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plot_mut_edM = combED_mutM[, i_extract]
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plot_wt_edM = combED_wtM[, i_extract]
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}else{
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cat("\nNo. of positions selected:", length(plot_positions))
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i_ofr = plot_positions[!plot_positions%in%msa_all_pos]
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cat("\n1 or more plot_positions out of range..."
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, "\nThese are:\n", i_ofr
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, "\nQuitting! Resubmit with correct plot_positions")
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quit()
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}
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}
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# Construct Y-axis for MSA mut plot:
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cat("\nCalculating y-axis for MSA mut plot")
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if (missing(y_breaks)){
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# Y-axis: Calculating
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cat("\n----------------------------------------"
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, "\nY-axis being generated from data"
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, "\n-----------------------------------------")
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ylim_low <- floor(min(combED_mutM)); ylim_low
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if( ylim_low == 0){
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ylim_low = ylim_low
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cat("\nY-axis lower limit:", ylim_low)
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y_rlow = seq(0, ylim_low, length.out = 3); y_rlow
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ylim_up <- ceiling(max(combED_mutM)) + 4; ylim_up
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cat("\nY-axis upper limit:", ylim_up)
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y_rup = seq(0, ylim_up, by = 2); y_rup
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}else{
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ylim_low = ylim_low + (-0.5)
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cat("\nY-axis lower limit is <0:", ylim_low)
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y_rlow = seq(0, ylim_low, length.out = 3); y_rlow
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ylim_up <- ceiling(max(combED_mutM)) + 3; ylim_up
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cat("\nY-axis upper limit:", ylim_up)
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y_rup = seq(0, ylim_up, by = 3); y_rup
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}
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#ylim_scale <- unique(sort(c(y_rlow, y_rup, ylim_up))); ylim_scale
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ylim_scale <- unique(sort(c(y_rlow, y_rup))); ylim_scale
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cat("\nY-axis generated: see below\n"
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, ylim_scale)
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}else{
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# Y-axis: User provided
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cat("\n--------------------------------"
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, "\nUsing y-axis:: User provided"
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,"\n---------------------------------")
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ylim_scale = sort(y_breaks)
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ylim_low = min(ylim_scale); ylim_low
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ylim_up = max(ylim_scale); ylim_up
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}
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######################################
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# Generating plots for muts and wt
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#####################################
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if (my_logo_col %in% c('clustalx','taylor')) {
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cat("\nSelected colour scheme:", my_logo_col
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, "\nUsing black theme\n")
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theme_bgc = "black"
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xfont_bgc = "white"
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yfont_bgc = "white"
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xtt_col = "white"
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ytt_col = "white"
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}
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if (my_logo_col %in% c('chemistry', 'hydrophobicity')) {
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cat("\nstart of MSA"
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, '\nSelected colour scheme:', my_logo_col
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, "\nUsing grey theme")
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theme_bgc = "grey"
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xfont_bgc = "black"
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yfont_bgc = "black"
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xtt_col = "black"
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ytt_col = "black"
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theme_bgc = "grey"
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xfont_bgc = "black"
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yfont_bgc = "black"
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xtt_col = "black"
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ytt_col = "black"
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}
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#####################################
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@ -272,6 +256,7 @@ else {
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, method = msa_method
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, col_scheme = my_logo_col
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, seq_type = 'auto') +
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theme(legend.position = leg_pos
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, legend.direction = leg_dir
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#, legend.title = element_blank()
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@ -295,17 +280,19 @@ else {
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, axis.title.y = element_text(size = y_tts
|
||||
, colour = ytt_col)
|
||||
, plot.background = element_rect(fill = theme_bgc))+
|
||||
xlab(x_lab)
|
||||
|
||||
xlab(x_lab_mut) + ylab(y_lab_mut)
|
||||
|
||||
if (missing(plot_positions)){
|
||||
ed_mut_logo_P = p0 +
|
||||
|
||||
ed_mut_logo_P = p0 +
|
||||
scale_x_discrete(breaks = msa_all_pos
|
||||
, expand = c(x_axis_offset,0)
|
||||
, expand = c(x_axis_offset, 0)
|
||||
, labels = msa_all_pos
|
||||
, limits = factor(msa_all_pos))+
|
||||
scale_y_continuous(limits = c(ylim_low, ylim_up)
|
||||
, breaks = ylim_scale
|
||||
, expand = c(0,y_axis_offset)) +
|
||||
, expand = c(0, y_axis_offset)) +
|
||||
geom_hline(yintercept = 0
|
||||
, linetype = "solid"
|
||||
, color = "grey"
|
||||
|
|
@ -313,20 +300,19 @@ else {
|
|||
|
||||
}else{
|
||||
ed_mut_logo_P = p0 +
|
||||
#scale_y_continuous(expand = c(0,0.09)) +
|
||||
scale_y_continuous(limits = c(ylim_low, ylim_up)
|
||||
, breaks = ylim_scale
|
||||
, expand = c(0,y_axis_offset))+
|
||||
scale_x_discrete(breaks = i_extract
|
||||
scale_x_discrete(breaks = i_extract
|
||||
, expand = c(x_axis_offset_filtered,0)
|
||||
, labels = i_extract
|
||||
, limits = factor(i_extract)) +
|
||||
#scale_y_continuous(expand = c(0,0.09)) +
|
||||
scale_y_continuous(limits = c(ylim_low, ylim_up)
|
||||
, breaks = ylim_scale
|
||||
, expand = c(0, y_axis_offset))+
|
||||
geom_hline(yintercept = 0
|
||||
, linetype = "solid"
|
||||
, color = "grey"
|
||||
, size = 1)
|
||||
|
||||
}
|
||||
, color = "grey"
|
||||
, size = 1)
|
||||
}
|
||||
|
||||
cat('\nDone: MSA plot for mutations')
|
||||
#return(msa_mut_logoP)
|
||||
|
|
@ -361,22 +347,25 @@ else {
|
|||
, colour = ytt_col)
|
||||
|
||||
, plot.background = element_rect(fill = theme_bgc)) +
|
||||
|
||||
ylab("") + xlab("Wild-type position")
|
||||
|
||||
if (missing(plot_positions)){
|
||||
|
||||
# No y-axis needed
|
||||
ed_wt_logo_P = p1 +
|
||||
scale_x_discrete(breaks = wt_all_pos
|
||||
, expand = c(x_axis_offset,0)
|
||||
, expand = c(x_axis_offset, 0)
|
||||
, labels = wt_all_pos
|
||||
, limits = factor(wt_all_pos))
|
||||
}else{
|
||||
|
||||
ed_wt_logo_P = p1 +
|
||||
scale_y_continuous(expand = c(0,0.09)) +
|
||||
scale_x_discrete(breaks = i_extract
|
||||
, expand = c(x_axis_offset_filtered, 0)
|
||||
, labels = i_extract
|
||||
, limits = factor(i_extract))
|
||||
}
|
||||
}
|
||||
|
||||
cat('\nDone: MSA plot for WT')
|
||||
#return(msa_wt_logoP)
|
||||
|
|
|
|||
|
|
@ -1,23 +1,30 @@
|
|||
#logo plots
|
||||
#####################################################################################
|
||||
# LogoPlotMSA():
|
||||
# Input:
|
||||
# Data:
|
||||
# msaSeq_mut: MSA chr vector for muts
|
||||
# msaSeq_wt [Optional]: MSA chr vector for wt
|
||||
|
||||
# one for multiple muts
|
||||
# --> select/drop down option to filter count of nsSNPs
|
||||
# --> select/drop down option for colour
|
||||
# --> should include WT
|
||||
# Others params:
|
||||
# plot_positions: can choose what positions to plot
|
||||
# msa_method : can be "bits" or "probability"
|
||||
# my_logo_col : can be "chemistry", "hydrophobicity", "taylor" or "clustalx"
|
||||
|
||||
# Data used
|
||||
# Returns data LogoPlot from MSA
|
||||
|
||||
#tab_mt # mutant logo plot
|
||||
#tab_wt # wt logo plot
|
||||
#...
|
||||
|
||||
# TODO: SHINY
|
||||
# drop down: my_logo_col i.e the 4 colour choices
|
||||
# drop down: for DataED_PFM(), ED score options:
|
||||
# c("log", log-odds", "diff", "probKL", "ratio", "unscaled_log", "wKL")
|
||||
# drop down/enter field: for DataED_PFM(), background probability
|
||||
# Make it hover over position and then get the corresponding data table!
|
||||
#%%======================================================================
|
||||
###################################################################################
|
||||
|
||||
#==================
|
||||
# logo data: OR
|
||||
#==================
|
||||
# NOTE: my_logo_col
|
||||
|
||||
LogoPlotMSA <- function(msaSeq_mut
|
||||
, msaSeq_wt
|
||||
, plot_positions
|
||||
|
|
@ -51,15 +58,15 @@ LogoPlotMSA <- function(msaSeq_mut
|
|||
cat("\n======================="
|
||||
, "\nPlotting entire MSA"
|
||||
, "\n========================")
|
||||
msa_seq_plot = msaSeq_mut
|
||||
msa_all_interim = sapply(msa_seq_plot, function(x) unlist(strsplit(x,"")))
|
||||
msa_seq_plot = msaSeq_mut
|
||||
msa_all_interim = sapply(msa_seq_plot, function(x) unlist(strsplit(x,"")))
|
||||
msa_all_interimDF = data.frame(msa_all_interim)
|
||||
msa_all_pos = as.numeric(rownames(msa_all_interimDF))
|
||||
msa_all_pos = as.numeric(rownames(msa_all_interimDF))
|
||||
|
||||
wt_seq_plot = msaSeq_wt
|
||||
wt_all_interim = sapply(wt_seq_plot, function(x) unlist(strsplit(x,"")))
|
||||
wt_all_interimDF = data.frame(wt_all_interim)
|
||||
wt_all_pos = as.numeric(rownames(wt_all_interimDF))
|
||||
wt_seq_plot = msaSeq_wt
|
||||
wt_all_interim = sapply(wt_seq_plot, function(x) unlist(strsplit(x,"")))
|
||||
wt_all_interimDF = data.frame(wt_all_interim)
|
||||
wt_all_pos = as.numeric(rownames(wt_all_interimDF))
|
||||
|
||||
|
||||
} else {
|
||||
|
|
@ -1,12 +1,12 @@
|
|||
#source("~/git/LSHTM_analysis/config/gid.R")
|
||||
source("~/git/LSHTM_analysis/config/pnca.R")
|
||||
#source("~/git/LSHTM_analysis/config/pnca.R")
|
||||
#source("~/git/LSHTM_analysis/config/embb.R")
|
||||
#source("~/git/LSHTM_analysis/config/katg.R")
|
||||
#source("~/git/LSHTM_analysis/config/alr.R")
|
||||
#source("~/git/LSHTM_analysis/config/rpob.R")
|
||||
#---------------------------------------------------
|
||||
source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
#
|
||||
#source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
||||
|
||||
################################
|
||||
# Logo plot with custom Y axis
|
||||
# mainly OR
|
||||
|
|
@ -61,7 +61,6 @@ source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
|||
# , leg_ts = 14 # leg text size
|
||||
# , leg_tts = 16 # leg title size
|
||||
# )
|
||||
#
|
||||
|
||||
########################################
|
||||
# Logo plot MSA
|
||||
|
|
@ -71,31 +70,84 @@ source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
|
|||
# specify {plot_positions}
|
||||
# To plot entire MSA, simply don't specify {plot_positions}
|
||||
# script: logoP_msa.R
|
||||
# TODO perhaps: ED logo from Logolas
|
||||
# TODO: Add scaled data option
|
||||
########################################
|
||||
LogoPlotMSA(msaSeq_mut = msa_seq
|
||||
, msaSeq_wt = wt_seq
|
||||
, msa_method = 'bits' # or probability
|
||||
, my_logo_col = "taylor"
|
||||
, plot_positions = active_aa_pos
|
||||
, x_lab = "nsSNP position"
|
||||
, y_lab = ""
|
||||
, x_ats = 10 # text size
|
||||
, x_tangle = 90 # text angle
|
||||
, x_axis_offset = 0.05
|
||||
, y_ats = 15
|
||||
, y_tangle = 0
|
||||
, x_tts = 13 # title size
|
||||
, y_tts = 15
|
||||
, leg_pos = "top" # can be top, left, right and bottom or c(0.8, 0.9)
|
||||
, leg_dir = "horizontal" #can be vertical or horizontal
|
||||
, leg_ts = 16 # leg text size
|
||||
, leg_tts = 16 # leg title size
|
||||
)
|
||||
# LogoPlotMSA(msaSeq_mut = msa_seq
|
||||
# , msaSeq_wt = wt_seq
|
||||
# # , use_pfm
|
||||
# # , use_pfm_scaled
|
||||
# # , use_ed
|
||||
# , msa_method = 'bits' # or probability
|
||||
# , my_logo_col = "taylor"
|
||||
# , plot_positions = 1:15
|
||||
# , x_lab = "nsSNP position"
|
||||
# , y_lab = ""
|
||||
# , x_ats = 10 # text size
|
||||
# , x_tangle = 90 # text angle
|
||||
# , x_axis_offset = 0.05
|
||||
# , y_ats = 15
|
||||
# , y_tangle = 0
|
||||
# , x_tts = 13 # title size
|
||||
# , y_tts = 15
|
||||
# , leg_pos = "top" # can be top, left, right and bottom or c(0.8, 0.9)
|
||||
# , leg_dir = "horizontal" #can be vertical or horizontal
|
||||
# , leg_ts = 16 # leg text size
|
||||
# , leg_tts = 16 # leg title size
|
||||
# )
|
||||
|
||||
########################################
|
||||
# ED Logo plot MSA
|
||||
# Mutant and wild-type
|
||||
########################################
|
||||
# library(Logolas)
|
||||
# library(ggseqlogo)
|
||||
# source("~/git/LSHTM_analysis/scripts/functions/my_logolas.R")
|
||||
# source("~/git/LSHTM_analysis/scripts/functions/logoP_logolas.R")
|
||||
#
|
||||
# # data msa: mut
|
||||
# my_data = read.csv("/home/tanu/git/Misc/practice_plots/pnca_msa_eg2.csv", header = F) #15 cols only
|
||||
# msaSeq_mut = my_data$V1
|
||||
# msa_seq = msaSeq_mut
|
||||
#
|
||||
# # data msa: wt
|
||||
# gene = "pncA"
|
||||
# drug = "pyrazinamide"
|
||||
# indir = paste0("~/git/Data/", drug , "/input/")
|
||||
#
|
||||
# in_filename_fasta = paste0(tolower(gene), "2_f2.fasta")
|
||||
# infile_fasta = paste0(indir, in_filename_fasta)
|
||||
# cat("\nInput fasta file for WT: ", infile_fasta, "\n")
|
||||
#
|
||||
# msa2 = read.csv(infile_fasta, header = F)
|
||||
# head(msa2)
|
||||
# cat("\nLength of WT fasta:", nrow(msa2))
|
||||
# wt_seq = msa2$V1
|
||||
# head(wt_seq)
|
||||
# msaSeq_wt = msa2$V1
|
||||
# wt_seq = msaSeq_wt
|
||||
|
||||
#PlotLogolasMSA()
|
||||
PlotLogolasMSA(msaSeq_mut = msa_seq
|
||||
, msaSeq_wt = wt_seq
|
||||
, logo_type = c("bits_pfm") # "EDLogo", bits_pfm", "probability_pfm", "bits_raw", "probability_raw") # can be "bits", "probability" or "custom"
|
||||
, EDScore_type = c("log") # see if this relevant, or source function should have it!
|
||||
, bg_prob = NULL
|
||||
, my_logo_col = "taylor"
|
||||
, plot_positions = c(1:15)
|
||||
#, y_breaks
|
||||
, x_lab_mut = "nsSNP-position"
|
||||
#, y_lab_mut
|
||||
, x_ats = 13 # text size
|
||||
, x_tangle = 90 # text angle
|
||||
, x_axis_offset = 0.05
|
||||
, x_axis_offset_filtered = 0.05
|
||||
, y_axis_offset = 0.05
|
||||
, y_ats = 13
|
||||
, y_tangle = 0
|
||||
, x_tts = 13
|
||||
, y_tts = 13
|
||||
, leg_pos = "top" # can be top, left, right and bottom or c(0.8, 0.9)
|
||||
, leg_dir = "horizontal" #can be vertical or horizontal
|
||||
, leg_ts = 16 # leg text size
|
||||
, leg_tts = 16 # leg title size
|
||||
)
|
||||
|
|
|
|||
|
|
@ -174,6 +174,7 @@ if(!require(protr)){
|
|||
|
||||
#BiocManager::install("Logolas")
|
||||
library("Logolas")
|
||||
library("Biostrings")
|
||||
|
||||
|
||||
####################################
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue