wideP_consurf3
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1 changed files with 193 additions and 192 deletions
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@ -1,29 +1,29 @@
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#####################################################################################
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# LogoPlotMSA():
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# Input:
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# Data:
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# msaSeq_mut: MSA chr vector for muts
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# msaSeq_wt: MSA chr vector for wt
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# Data:
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# msaSeq_mut: MSA chr vector for muts
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# msaSeq_wt: MSA chr vector for wt
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# Logo type params:
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# logo_type = c("EDLogo", "bits_pfm", "probability_pfm", "bits_raw", "probability_raw")
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# EDLogo: calculated from the Logolas package based on PFM matrix (scaled).
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#The required content from the package is sourced locally within 'my_logolas.R'
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# bits_pfm: Information Content based on PFM scaled matrix (my_logolas.R)
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# probability_pfm: Probability based on PFM scaled matrix (my_logolas.R)
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# bits_raw: Information Content based on Raw MSA (ggseqlogo)
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# probability_raw: Probability based on Raw MSA (ggseqlogo)
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# Logo type params:
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# logo_type = c("EDLogo", "bits_pfm", "probability_pfm", "bits_raw", "probability_raw")
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# EDLogo: calculated from the Logolas package based on PFM matrix (scaled).
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#The required content from the package is sourced locally within 'my_logolas.R'
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# bits_pfm: Information Content based on PFM scaled matrix (my_logolas.R)
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# probability_pfm: Probability based on PFM scaled matrix (my_logolas.R)
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# bits_raw: Information Content based on Raw MSA (ggseqlogo)
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# probability_raw: Probability based on Raw MSA (ggseqlogo)
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# EDScore_type = c("log", log-odds", "diff", "probKL", "ratio", "unscaled_log", "wKL")
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# bg_prob: background probability, default is equal i.e NULL.
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# This is used by the internal call to DataED_PFM(). This func takes thse args. I have used it here for
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# completeness and allow nuanced plot control
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# EDScore_type = c("log", log-odds", "diff", "probKL", "ratio", "unscaled_log", "wKL")
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# bg_prob: background probability, default is equal i.e NULL.
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# This is used by the internal call to DataED_PFM(). This func takes thse args. I have used it here for
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# completeness and allow nuanced plot control
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# my_logo_col = c("chemistry", "hydrophobicity", "clustalx", "taylor")
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# --> if clustalx and taylor, set variable to black bg + white font
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# --> if chemistry and hydrophobicity, then grey bg + black font
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# my_logo_col = c("chemistry", "hydrophobicity", "clustalx", "taylor")
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# --> if clustalx and taylor, set variable to black bg + white font
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# --> if chemistry and hydrophobicity, then grey bg + black font
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# ...other params
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# ...other params
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# Returns: Logo plots from MSA both mutant and wt (for comparability)
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# For my case, I always use it as it helps see what is at the wild-type already!
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@ -62,7 +62,7 @@ LogoPlotMSA <- function(unified_msa
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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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)
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)
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{
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# FIXME: Hack!
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@ -71,7 +71,7 @@ LogoPlotMSA <- function(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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# Get PFM matrix for mut and wt MSA provided
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# Get PFM matrix for mut and wt MSA provided
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data_ed = DataED_PFM(msaSeq_mut
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, msaSeq_wt
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, ED_score = EDScore_type)
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@ -163,7 +163,7 @@ LogoPlotMSA <- function(unified_msa
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wt_interimDF = data.frame(wt_interim)
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wt_pos = as.numeric(rownames(wt_interimDF))
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}
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}
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if (logo_type == "probability_raw"){
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msa_method = "probability"
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@ -186,126 +186,126 @@ LogoPlotMSA <- function(unified_msa
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if(missing(plot_positions)){
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#================================
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# NO filtering of positions
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#================================
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#---------
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# MSA mut
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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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#================================
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# NO filtering of positions
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#================================
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#---------
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# MSA mut
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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 = data_logo_mut
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plot_mut_edM = data_logo_mut
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#---------
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# MSA WT
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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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#---------
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# MSA WT
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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 = data_logo_wt
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plot_wt_edM = data_logo_wt
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}else{
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#================================
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# Filtering of 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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#================================
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# Filtering of 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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plot_positions = sort(plot_positions)
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cat("\nPlotting positions sorted:\n"
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, 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_pos) && all(plot_positions%in%wt_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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if ( all(plot_positions%in%msa_pos) && all(plot_positions%in%wt_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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#-----------------
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# PFM: mut + wt
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#------------------
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if (logo_type%in%c("EDLogo", "bits_pfm", "probability_pfm")){
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#-----------------
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# PFM: mut + wt
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#------------------
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if (logo_type%in%c("EDLogo", "bits_pfm", "probability_pfm")){
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plot_mut_edM = data_logo_mut[, i_extract]
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plot_wt_edM = data_logo_wt[, i_extract]
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plot_mut_edM = data_logo_mut[, i_extract]
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plot_wt_edM = data_logo_wt[, i_extract]
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}
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if (logo_type%in%c("bits_raw", "probability_raw")){
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#--------
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# Mut
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#--------
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dfP1 = msa_interimDF[i_extract,]
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dfP1 = data.frame(t(dfP1))
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names(dfP1) = i_extract
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cols_to_paste = names(dfP1)
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dfP1['chosen_seq'] = apply(dfP1[, cols_to_paste]
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, 1
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, paste, sep = ''
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, collapse = "")
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plot_mut_edM = dfP1$chosen_seq
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#--------
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# WT
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#--------
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dfP2 = wt_interimDF[i_extract,]
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dfP2 = data.frame(t(dfP2))
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names(dfP2) = i_extract
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cols_to_paste2 = names(dfP2)
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dfP2['chosen_seq'] = apply( dfP2[, cols_to_paste2]
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, 1
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, paste, sep = ''
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, collapse = "")
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plot_wt_edM = dfP2$chosen_seq
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}
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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_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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if (logo_type%in%c("bits_raw", "probability_raw")){
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#--------
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# Mut
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#--------
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dfP1 = msa_interimDF[i_extract,]
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dfP1 = data.frame(t(dfP1))
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names(dfP1) = i_extract
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cols_to_paste = names(dfP1)
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dfP1['chosen_seq'] = apply(dfP1[, cols_to_paste]
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, 1
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, paste, sep = ''
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, collapse = "")
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plot_mut_edM = dfP1$chosen_seq
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#--------
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# WT
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#--------
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dfP2 = wt_interimDF[i_extract,]
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dfP2 = data.frame(t(dfP2))
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names(dfP2) = i_extract
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cols_to_paste2 = names(dfP2)
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dfP2['chosen_seq'] = apply( dfP2[, cols_to_paste2]
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, 1
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, paste, sep = ''
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, collapse = "")
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plot_wt_edM = dfP2$chosen_seq
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}
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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_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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######################################
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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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######################################
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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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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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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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@ -335,11 +335,11 @@ LogoPlotMSA <- function(unified_msa
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, vjust = 0.4
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, colour = xfont_bgc)
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#, axis.text.y = element_blank()
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, axis.text.y = element_text(size = y_ats
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, angle = y_tangle
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, hjust = 1
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, vjust = -1.0
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, colour = yfont_bgc)
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, axis.text.y = element_text(size = y_ats
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, angle = y_tangle
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, hjust = 1
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, vjust = -1.0
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, colour = yfont_bgc)
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, axis.title.x = element_text(size = x_tts
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, colour = xtt_col)
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, axis.title.y = element_text(size = y_tts
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@ -349,14 +349,14 @@ LogoPlotMSA <- function(unified_msa
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xlab(x_lab_mut)
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if (missing(plot_positions)){
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ed_mut_logo_P = p0 +
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ed_mut_logo_P = p0 +
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scale_x_discrete(breaks = msa_pos
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, expand = c(x_axis_offset, 0)
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, labels = msa_pos
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, limits = factor(msa_pos))
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}else{
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ed_mut_logo_P = p0 +
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ed_mut_logo_P = p0 +
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scale_x_discrete(breaks = i_extract
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, expand = c(x_axis_offset_filtered, 0)
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, labels = i_extract
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@ -366,20 +366,20 @@ LogoPlotMSA <- function(unified_msa
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if (logo_type == "EDLogo"){
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ed_mut_logo_P = ed_mut_logo_P +
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scale_y_continuous(limits = c(ylim_low, ylim_up)
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, breaks = ylim_scale
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, expand = c(0, y_axis_offset)) +
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geom_hline(yintercept = 0
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, linetype = "solid"
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, color = "grey"
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, size = 1)
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scale_y_continuous(limits = c(ylim_low, ylim_up)
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, breaks = ylim_scale
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, expand = c(0, y_axis_offset)) +
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geom_hline(yintercept = 0
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, linetype = "solid"
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, color = "grey"
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, size = 1)
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}
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if (missing(y_lab_mut)){
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ed_mut_logo_P = ed_mut_logo_P + ylab(y_label)
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} else{
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ed_mut_logo_P = ed_mut_logo_P + ylab(y_lab_mut)
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}
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ed_mut_logo_P = ed_mut_logo_P + ylab(y_label)
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} else{
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ed_mut_logo_P = ed_mut_logo_P + ylab(y_lab_mut)
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}
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cat('\nDone: MSA plot for mutations')
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#return(msa_mut_logoP)
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@ -415,24 +415,24 @@ LogoPlotMSA <- function(unified_msa
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, plot.background = element_rect(fill = theme_bgc)) +
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ylab("") + xlab("Wild-type position")
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ylab("") + xlab("Wild-type position")
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if (missing(plot_positions)){
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if (missing(plot_positions)){
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# No y-axis needed
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ed_wt_logo_P = p1 +
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scale_x_discrete(breaks = wt_pos
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, expand = c(x_axis_offset, 0)
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, labels = wt_pos
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, limits = factor(wt_pos))
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}else{
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# No y-axis needed
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ed_wt_logo_P = p1 +
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scale_x_discrete(breaks = wt_pos
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, expand = c(x_axis_offset, 0)
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, labels = wt_pos
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, limits = factor(wt_pos))
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}else{
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ed_wt_logo_P = p1 +
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scale_x_discrete(breaks = i_extract
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, expand = c(x_axis_offset_filtered, 0)
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, labels = i_extract
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, limits = factor(i_extract))
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}
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ed_wt_logo_P = p1 +
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scale_x_discrete(breaks = i_extract
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, expand = c(x_axis_offset_filtered, 0)
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, labels = i_extract
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, limits = factor(i_extract))
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}
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cat('\nDone: MSA plot for WT')
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#return(msa_wt_logoP)
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@ -451,10 +451,11 @@ LogoPlotMSA <- function(unified_msa
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#svg(LogoSNPs_combined, width = 32, height = 10)
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LogoED_comb = cowplot::plot_grid(PlotlogolasL[['ed_mut_logoP']]
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, PlotlogolasL[['ed_wt_logoP']]
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, nrow = 2
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, align = "v"
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, rel_heights = c(3/4, 1/4))
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, PlotlogolasL[['ed_wt_logoP']]
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, nrow = 2
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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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return(LogoED_comb)
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