added placeholder defaults for functions in R to make sure that R shiny layput works with a data set for meeting tomorrow

This commit is contained in:
Tanushree Tunstall 2022-02-14 19:33:00 +00:00
parent 0460ca1708
commit d38521e03a
11 changed files with 120 additions and 83 deletions

View file

@ -4,11 +4,11 @@
# Lineage Diversity barplot
########################################
lin_count_bp <- function( lf_data
, x_categ = ""
, y_count = ""
, bar_fill_categ = ""
, display_label_col = ""
lin_count_bp <- function( lf_data = lin_lf
, x_categ = "sel_lineages"
, y_count = "p_count"
, bar_fill_categ = "count_categ"
, display_label_col = "p_count"
, bar_stat_stype = "identity"
, x_lab_angle = 90
, d_lab_size = 5
@ -20,13 +20,14 @@ lin_count_bp <- function( lf_data
, my_xals = 22 # x axis label size
, my_yals = 22 # y axis label size
, my_lls = 22 # legend label size
, bar_col_labels = ""
, bar_col_values = ""
, bar_col_labels = c("Mutations", "Total Samples")
, bar_col_values = c("grey50", "gray75")
, bar_leg_name = ""
, leg_location = "top"
, y_log10 = FALSE
, y_scale_percent = FALSE
, y_label = c("Count", "SNP diversity")
#, y_label = c("Count")
) {
g = ggplot(lf_data
, aes( x = factor( eval(parse(text = x_categ)), ordered = T )

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@ -36,9 +36,9 @@ ColourPalleteMulti = function(df, group, subgroup){
bp_stability_hmap <- function(plotdf = merged_df3
, xvar_colname = "position"
#, bar_col_colname = "group"
, stability_colname = ""
, stability_outcome_colname = ""
, p_title = "" # "Protein stability (DUET)"
, stability_colname = "duet_scaled"
, stability_outcome_colname = "duet_outcome"
, p_title = "DUET" # "Protein stability (DUET)"
, my_xaxls = 12 # x-axis label size
, my_yaxls = 20 # y-axis label size
, my_xaxts = 18 # x-axis text size

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@ -12,7 +12,7 @@
# wideP():
# input args
#==========================================================
wideP_point <- function(plotdf
wideP_consurf <- function(plotdf
, xvar_colname = "position"
, yvar_colname = "consurf_score"
, yvar_colourN_colname = "consurf_colour_rev" # num from 0-1
@ -542,24 +542,51 @@ wideP_point <- function(plotdf
}else{
cat("\nNo annotation for xvar requested")
}
#==============================================
if (A_xvar_lig){
legs = grid.arrange(legend1
legs = cowplot::plot_grid(legend1
, legend2
, ncol = 1
, heights = c(3/4,1))
out2 = grid.arrange( out + theme(legend.position = "none")
, align = "hv"
, rel_heights = c(3/4,1))
out2 = cowplot::plot_grid( out + theme(legend.position = "none")
, legs
, ncol = 2
, widths = c(9/10, 0.5/10)
, align = "hv"
, rel_widths = c(9/10, 0.5/10)
)
}else{
out2 = grid.arrange( out + theme(legend.position = "none")
out2 = cowplot::plot_grid( out + theme(legend.position = "none")
, legend1
, ncol = 2
, widths = c(9/10, 0.5/10)
, align = "hv"
, rel_widths = c(9/10, 0.5/10)
)
}
#==============================================
#==============================================
# if (A_xvar_lig){
# legs = grid.arrange(legend1
# , legend2
# , ncol = 1
# , heights = c(3/4,1))
#
# out2 = grid.arrange( out + theme(legend.position = "none")
# , legs
# , ncol = 2
# , widths = c(9/10, 0.5/10)
# )
# }else{
# out2 = grid.arrange( out + theme(legend.position = "none")
# , legend1
# , ncol = 2
# , widths = c(9/10, 0.5/10)
# )
# }
#==============================================
return(out2)
#return(out2)

View file

@ -6,10 +6,10 @@
# beeswarm
#############################
lf_bp <- function(lf_df
, p_title = ""
, colour_categ = ""
, x_grp = "mutation_info"
lf_bp <- function(lf_df = lf_duet
, p_title = "DUET-DDG"
, colour_categ = "duet_outcome"
, x_grp = "mutation_info_labels"
, y_var = "param_value"
, facet_var = "param_type"
, n_facet_row = 1

View file

@ -15,8 +15,8 @@ theme_set(theme_grey())
## ...opt args
#==========================================================
stability_count_bp <- function(plotdf
, df_colname = ""
, leg_title = "Legend Title"
, df_colname = "duet_outcome"
, leg_title = "DUET"
, ats = 25 # axis text size
, als = 22 # axis label size
, lts = 20 # legend text size

View file

@ -5,15 +5,14 @@ getwd()
#===========================================
# load functions, data, dirs, hardocded vars
# that will be used in testing the functions
#drug = "streptomycin"
#gene = "gid"
#source("plotting_data.R")
#infile = paste0("~/git/Data/", drug, "/output/", gene, "_comb_stab_struc_params.csv")
#infile_df = read.csv(infile)
#===========================================
drug = "streptomycin"
gene = "gid"
source("plotting_data.R")
infile = paste0("~/git/Data/", drug, "/output/", gene, "_comb_stab_struc_params.csv")
infile_df = read.csv(infile)
lig_dist = 5
pd_df = plotting_data(infile_df
, lig_dist_colname = 'ligand_distance'
@ -42,8 +41,8 @@ print(paste0("plot filename:", basic_bp_duet))
# function only
stability_count_bp(plotdf = my_df_u
, df_colname = "duet_outcome"
, leg_title = "DUET outcome"
, df_colname = "ligand_outcome"
, leg_title = "Lig outcome"
, label_categories = c("Destabilising", "Stabilising")
, leg_position = "top")

View file

@ -20,8 +20,8 @@ levels(lin_lf_plot$sel_lineages_f)
#=========================
# Lineage count plot
#=========================
lin_count_bp(lin_lf_plot
, x_categ = "sel_lineages_f"
lin_count_bp(lin_lf_plot = lin_lf
, x_categ = "sel_lineages"
, y_count = "p_count"
, bar_fill_categ = "count_categ"
, display_label_col = "p_count"
@ -51,8 +51,8 @@ levels(lin_wf_plot$sel_lineages_f)
#=========================
# Lineage Diversity plot
#=========================
lin_count_bp(lin_wf_plot
, x_categ = "sel_lineages_f"
lin_count_bp(lin_wf_plot = lin_wf
, x_categ = "sel_lineages"
, y_count = "snp_diversity"
, display_label_col = "snp_diversity_f"
, bar_stat_stype = "identity"

View file

@ -4,9 +4,9 @@ library(ggplot2)
library(tidyverse)
library(cowplot)
library(gridExtra)
source("consurf_plot_func.R")
source("~/git/LSHTM_analysis/scripts/functions/consurfP.R")
# ###########################################################################
############################################################################
# merged_df3 = read.csv("~/git/Data/cycloserine/output/alr_all_params.csv"); source("~/git/LSHTM_analysis/config/alr.R")
# if ( tolower(gene) == "alr") {
# aa_pos_lig1 = NULL
@ -15,13 +15,13 @@ source("consurf_plot_func.R")
# p_title = gene
# }
###########################################################################
# merged_df3 = read.csv("~/git/Data/ethambutol/output/embb_all_params.csv"); source("~/git/LSHTM_analysis/config/embb.R")
# if ( tolower(gene) == "embb") {
# aa_pos_lig1 = aa_pos_ca
# aa_pos_lig2 = aa_pos_cdl
# aa_pos_lig3 = aa_pos_dsl
# p_title = gene
# }
merged_df3 = read.csv("~/git/Data/ethambutol/output/embb_all_params.csv"); source("~/git/LSHTM_analysis/config/embb.R")
if ( tolower(gene) == "embb") {
aa_pos_lig1 = aa_pos_ca
aa_pos_lig2 = aa_pos_cdl
aa_pos_lig3 = aa_pos_dsl
p_title = gene
}
###########################################################################
# merged_df3 = read.csv("~/git/Data/streptomycin/output/gid_all_params.csv"); source("~/git/LSHTM_analysis/config/gid.R")
# if ( tolower(gene) == "gid") {
@ -47,13 +47,13 @@ source("consurf_plot_func.R")
# p_title = gene
# }
###########################################################################
merged_df3 = read.csv("~/git/Data/rifampicin/output/rpob_all_params.csv"); source("~/git/LSHTM_analysis/config/rpob.R")
if ( tolower(gene) == "rpob") {
aa_pos_lig1 = NULL
aa_pos_lig2 = NULL
aa_pos_lig3 = NULL
p_title = gene
}
# merged_df3 = read.csv("~/git/Data/rifampicin/output/rpob_all_params.csv"); source("~/git/LSHTM_analysis/config/rpob.R")
# if ( tolower(gene) == "rpob") {
# aa_pos_lig1 = NULL
# aa_pos_lig2 = NULL
# aa_pos_lig3 = NULL
# p_title = gene
# }
#########################################################################
consurf_palette1 = c("0" = "yellow2"
@ -84,21 +84,21 @@ consurf_palette2 = c("0" = "yellow2"
aa_pos_hbond = c(2, 4)
aa_pos_other = c(3, 4, 14, 10)
wideP_point (plotdf = merged_df3
wideP_consurf(plotdf = merged_df3
, xvar_colname = "position"
, yvar_colname = "consurf_score"
, yvar_colourN_colname = "consurf_colour_rev"
, ylab = "Consurf score"
, plot_error_bars = F
, plot_error_bars = T
, upper_EB_colname = "consurf_ci_upper"
, lower_EB_colname = "consurf_ci_lower"
, plot_type = "point"
, point_colours = consurf_palette2
, leg_title1 = "Consurf"
, leg_labels = c("0"="Insufficient Data"
, "1"= "Variable"
, "1" = "Variable"
, "2", "3", "4", "5", "6", "7", "8"
, "9"= "Conserved")
, "9" = "Conserved")
# axes title and label sizes
, x_axts = 8

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@ -5,3 +5,4 @@ source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
m3 = corr_data_extract(merged_df3); head(m3)
m2 = corr_data_extract(meregd_df2); head(m2)
m3S = corr_data_extract(merged_df3, extract_scaled_cols = T); head(m3S)

View file

@ -15,7 +15,7 @@ source("../functions/lf_bp.R")
lf_bp(lf_df = lf_encomddg
, p_title = "ENCoM-DDG"
, colour_categ = "ddg_encom_outcome"
, x_grp = "mutation_info"
, x_grp = "mutation_info_labels"
, y_var = "param_value"
, facet_var = "param_type"
, n_facet_row = 1

View file

@ -1,5 +1,5 @@
source("~/git/LSHTM_analysis/config/gid.R")
#source("~/git/LSHTM_analysis/config/pnca.R")
#source("~/git/LSHTM_analysis/config/gid.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")
@ -12,7 +12,7 @@ source("~/git/LSHTM_analysis/scripts/plotting/get_plotting_dfs.R")
# mainly OR
# script: logoP_or.R
################################
LogoPlotCustomH (plot_df = merged_df3
LP1<- LogoPlotCustomH (plot_df = merged_df3
, x_axis_colname = "position"
, y_axis_colname = "or_mychisq"
, symbol_colname = "mutant_type"
@ -25,10 +25,10 @@ LogoPlotCustomH (plot_df = merged_df3
, y_lab = "Odds Ratio"
, x_ats = 10 # text size
, x_tangle = 90 # text angle
, y_ats = 22
, y_ats = 15
, y_tangle = 0
, x_tts = 19 # title size
, y_tts = 22
, x_tts = 13 # title size
, y_tts = 13
#, leg_pos = c(0.05,-0.12)
, leg_pos = "top"
, leg_dir = "horizontal"
@ -36,30 +36,29 @@ LogoPlotCustomH (plot_df = merged_df3
, leg_tts = 16 # leg title size
)
########################################
# Logo plot showing nsSNPs by positions
# wild-type and mutant aa
# script: logoP_snp.R
########################################
LogoPlotSnps(plot_df = merged_df3
LP2<- LogoPlotSnps(plot_df = merged_df3
, x_axis_colname = "position"
, symbol_mut_colname = "mutant_type"
, symbol_wt_colname = "wild_type"
, omit_snp_count = c(1)# can be 0,1, 2, etc.
, my_logo_col = "chemistry"
, omit_snp_count = c(1)# can be 0,1, 2, etc.# DD
, my_logo_col = "chemistry" #DD
, x_lab = "Wild-type position"
, y_lab = "nsSNP count"
, x_ats = 10 # text size
, x_tangle = 90 # text angle
, y_ats = 18
, x_ats = 10
, x_tangle = 90
, y_ats = 15
, y_tangle = 0
, x_tts = 18 # title size
, y_tts = 18
, 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 = 14 # leg text size
, leg_tts = 16 # leg title size
, leg_ts = 14
, leg_tts = 16
)
####################################################
@ -76,13 +75,12 @@ LogoPlotSnps(plot_df = merged_df3
# to select a small dataset: see test_ed_pfm_data.R
#####################################################
LogoPlotMSA(msaSeq_mut = msa_seq
LP3<- LogoPlotMSA(msaSeq_mut = msa_seq
, msaSeq_wt = wt_seq
, logo_type = c("EDLogo") # "EDLogo", bits_pfm", "probability_pfm", "bits_raw", "probability_raw")
, EDScore_type = c("log")
, bg_prob = NULL
, my_logo_col = "taylor"
, my_logo_col = "chemistry"
#, plot_positions = c(5:10, 92, 195, 118:119)
, x_axis_offset = 0.02
, x_axis_offset_filtered = 0.05
@ -101,3 +99,14 @@ LogoPlotMSA(msaSeq_mut = msa_seq
, leg_ts = 16
, leg_tts = 16
)
out_logoP = cowplot::plot_grid(LP3, LP1, LP2
, nrow = 3
, ncol = 1
, rel_width = c(1/3, 0.5/3, 1/3)
, rel_heights = c(1, 1, 1)
, align = "hv")
out_logoP