tanu/LSHTM_analysis
1
0
Fork 0
Code Issues Pull requests Releases Wiki Activity

renamed file and updated logo plot code

Browse source
This commit is contained in:
Tanushree Tunstall 2020-02-26 12:00:32 +00:00
parent 95f0e28fb2
commit 61f8dc57c9
2 changed files with 96 additions and 117 deletions
Download patch file Download diff file Expand all files Collapse all files

211
mcsm_analysis/pyrazinamide/scripts/plotting/logo_plot_logolas.R → mcsm_analysis/pyrazinamide/scripts/plotting/logolas_logoplot.R
View file

@ -1,38 +1,37 @@
getwd() getwd()
setwd("~/git/LSHTM_Y1_PNCA/mcsm_analysis/pyrazinamide/Scripts/Plotting") setwd("~/git/LSHTM_analysis/mcsm_analysis/pyrazinamide/scripts/plotting/")
getwd() getwd()
######################################################################## ########################################################################
# Installing and loading required packages # # Installing and loading required packages #
######################################################################## ########################################################################
#source("../Header_TT.R") source("../Header_TT.R")
#source("barplot_colour_function.R") #source("barplot_colour_function.R")
#library(ggseqlogo) library(ggseqlogo)
######################################################################## #=======
# Read file: call script for combining df for lig # # input
######################################################################## #=======
#############
# msa file: output of generate_mut_sequences.py
#############
homedir = '~'
indir = 'git/Data/pyrazinamide/output'
in_filename = "gene_msa.txt"
infile = paste0(homedir, '/', indir,'/', in_filename)
print(infile)
#=======
# input
#=======
#############
# combined dfs
#############
source("../combining_two_df.R") source("../combining_two_df.R")
#---------------------- PAY ATTENTION
# the above changes the working dir
#[1] "/home/tanu/git/LSHTM_Y1_PNCA/mcsm_analysis/pyrazinamide/Scripts"
#---------------------- PAY ATTENTION
#==========================
# This will return:
#merged_df2 # 3092, 35
#merged_df2_comp #3012, 35
#merged_df3 #335, 35
#merged_df3_comp #293, 35
#==========================
########################### ###########################
# Data for Logo plots # Data for Logo plots
# you need big df i.e # you need big df i.e
@ -69,10 +68,40 @@ table(my_df$position == my_df$Position)
c1 = unique(my_df$Position) # 130 c1 = unique(my_df$Position) # 130
nrow(my_df) # 3092 nrow(my_df) # 3092
#FIXME
#!!! RESOLVE !!!
# get freq count of positions and add to the df
setDT(my_df)[, occurrence_sample := .N, by = .(id)]
table(my_df$occurrence_sample)
my_df2 = my_df %>%
select(id, Mutationinformation, Wild_type, WildPos, position, Mutant_type, occurrence, occurrence_sample)
write.csv(my_df2, "my_df2.csv")
# extract freq_pos>1 since this will not add to much in the logo plot # extract freq_pos>1 since this will not add to much in the logo plot
# pos 5 has one mutation but coming from atleast 5 samples?
table(my_df$occurrence)
foo = my_df[my_df$occurrence ==1,]
# uncomment as necessary
my_data_snp = my_df #3092
#!!! RESOLVE
# FIXME
my_data_snp = my_df[my_df$occurrence!=1,] #3072, 36...3019 my_data_snp = my_df[my_df$occurrence!=1,] #3072, 36...3019
u = unique(my_data_snp$Position) #96 u = unique(my_data_snp$Position) #96
######################################################################## ########################################################################
# end of data extraction and cleaning for plots # # end of data extraction and cleaning for plots #
######################################################################## ########################################################################
@ -94,79 +123,6 @@ u = unique(my_data_snp$Position) #96
##very good: http://www.cbs.dtu.dk/biotools/Seq2Logo-2.0/ ##very good: http://www.cbs.dtu.dk/biotools/Seq2Logo-2.0/
#############
#PLOTS: Bar plot with aa properties
#using gglogo
#useful links: https://stackoverflow.com/questions/5438474/plotting-a-sequence-logo-using-ggplot2
#############
#following example
require(ggplot2)
require(reshape2)
library(gglogo)
library(ggrepel)
#lmf <- melt(logodf, id.var='pos')
foo = my_data_snp[, c("Position"
, "Mutant_type"
, "ratioDUET"
, "OR"
, "mut_prop_polarity"
, "mut_prop_water") ]
head(foo) #3019, 6
foo = foo[order(foo$Position),]
head(foo)
##############
# ggseqlogo
#https://stackoverflow.com/questions/1439513/creating-a-sequential-list-of-letters-with-r
##############
# Some sample data for aa
data(ggseqlogo_sample)
seqs_aa = seqs_aa$AKT1
class(seqs_aa); str(seqs_aa)
# seq logo with custom x-axis
ggseqlogo( seqs_aa$AKT1, seq_type='aa'
, col_scheme = "hydrophobicity")+
theme(legend.position = "top")
#theme(axis.text.x = element_blank()) +
theme_logo()#+
#scale_x_continuous(breaks= 1:15
#, expand = c(0.105, 0)
# , labels = LETTERS[1:15]
##############
# ggseqlogo: custom matrix of my data
##############
snps = read.csv(#'../Data/snps_msa2.txt'
# '../Data/snps_msa.txt'
'../Data/gene_msa.txt'
, stringsAsFactors = F
, header = F) #3072,
class(snps)
snps2 = as.character(snps[1:nrow(snps),])
class(snps2); str(snps2)
ggseqlogo(snps2) # COMPLAINS about length of each sequence if snps_msa2 is used
#### NOT WORKING
#source("http://bioconductor.org/biocLite.R")
#install.packages("BiocManager")
#library(BiocManager)
BiocManager::install("Logolas")
#biocLite("Logolas")
library("Logolas")
#https://kkdey.github.io/Logolas-pages/workflow.html
# partially working
#============== #==============
# matrix for mutant type # matrix for mutant type
# frequency of mutant type by position # frequency of mutant type by position
@ -188,7 +144,7 @@ colnames(tab_mt) #pos
# Plot 1: mutant logo # Plot 1: mutant logo
#********************** #**********************
my_ymax = max(my_data_snp$occurrence); my_ymax my_ymax = max(my_data_snp$occurrence); my_ymax
my_ylim = c(0,my_ymax) my_ylim = c(0,my_ymax) # very important
# axis sizes # axis sizes
# common: text and label # common: text and label
@ -213,38 +169,38 @@ chemistry = data.frame(
stringsAsFactors = F stringsAsFactors = F
) )
# uncomment as necessary
my_type = "EDLogo"
my_type = "Logo"
# EDlogo
logomaker(tab_mt logomaker(tab_mt
, type = "EDLogo" , type = my_type
# , type = "Logo"
, return_heights = T , return_heights = T
, color_type = "per_row" # , color_type = "per_row"
, colors = chemistry$col # , colors = chemistry$col
# , method = 'custom' # , method = 'custom'
# , seq_type = 'aa' # , seq_type = 'aa'
# , col_scheme = "taylor" # , col_scheme = "taylor"
# , col_scheme = "chemistry2" # , col_scheme = "chemistry2"
) + ) +
theme(legend.position = "bottom" theme(legend.position = "bottom"
, legend.title = element_blank() , legend.title = element_blank()
, legend.text = element_text(size = my_lts) , legend.text = element_text(size = my_lts )
, axis.text.x = element_text(size = my_xats , angle = 90) , axis.text.x = element_text(size = my_ats , angle = 90)
# , axis.text.y = element_text(size = my_yats , angle = 90) , axis.text.y = element_text(size = my_ats , angle = 90))
)
p0 = logomaker(tab_mt p0 = logomaker(tab_mt
, type = "EDLogo" , type = my_type
, return_heights = T , return_heights = T
# , method = 'custom' , color_type = "per_row"
, colors = chemistry$col
# , seq_type = 'aa' # , seq_type = 'aa'
# , col_scheme = "taylor" # , col_scheme = "taylor"
# , col_scheme = "chemistry2" # , col_scheme = "chemistry2"
) + ) +
#ylab('my custom height') + #ylab('my custom height') +
theme(axis.text.x = element_blank()) + theme(axis.text.x = element_blank()) +
theme_logo()+ # theme_logo()+
# scale_x_continuous(breaks=1:51, parse (text = colnames(tab)) ) # scale_x_continuous(breaks=1:51, parse (text = colnames(tab)) )
scale_x_continuous(breaks = 1:ncol(tab_mt) scale_x_continuous(breaks = 1:ncol(tab_mt)
, labels = colnames(tab_mt))+ , labels = colnames(tab_mt))+
@ -256,23 +212,46 @@ p0
# further customisation # further customisation
p1 = p0 + theme(legend.position = "bottom" p1 = p0 + theme(legend.position = "bottom"
, legend.title = element_blank() , legend.title = element_blank()
, legend.text = element_text(size = leg_size) , legend.text = element_text(size = my_lts)
, axis.text.x = element_text(size = x_size , angle = 90) , axis.text.x = element_text(size = my_ats , angle = 90)
, axis.text.y = element_text(size = y_size , angle = 90)) , axis.text.y = element_text(size = my_ats , angle = 90))
p1 p1
#=======
# input
#=======
#############
# msa file: output of generate_mut_sequences.py
#############
homedir = '~'
indir = 'git/Data/pyrazinamide/output'
in_filename = "gene_msa.txt"
infile = paste0(homedir, '/', indir,'/', in_filename)
print(infile)
##### ##############
# ggseqlogo: custom matrix of my data
##############
snps = read.csv(infile
, stringsAsFactors = F
, header = F) #3072,
class(snps); str(snps) # df and chr
logomaker(snps2, type = "EDLogo" # turn to a character vector
, color_type = "per_symbol") + snps2 = as.character(snps[1:nrow(snps),])
class(snps2); str(snps2) #character, chr
# plot
logomaker(snps2, type = my_type
, color_type = "per_row") +
theme(axis.text.x = element_blank()) + theme(axis.text.x = element_blank()) +
theme_logo()+ theme_logo()+
# scale_x_continuous(breaks=1:51, parse (text = colnames(tab)) ) # scale_x_continuous(breaks=1:51, parse (text = colnames(tab)) )
scale_x_continuous(breaks = 1:ncol(tab_mt) scale_x_continuous(breaks = 1:ncol(tab_mt)
, labels = colnames(tab_mt))+ , labels = colnames(tab_mt))+
scale_y_continuous( breaks = 1:my_ymax scale_y_continuous( breaks = 0:5
, limits = my_ylim) , limits = my_ylim)

2
mcsm_analysis/pyrazinamide/scripts/plotting/snp_logo_plot.R
View file

@ -251,7 +251,7 @@ p2
p3 = p2 + p3 = p2 +
theme(legend.position = "bottom" theme(legend.position = "bottom"
, legend.text = element_text(size = my_lts) , legend.text = element_text(size = my_lts)
, axis.text.x = element_text(size = my_ats- , axis.text.x = element_text(size = my_ats
, angle = 90) , angle = 90)
, axis.text.y = element_blank()) , axis.text.y = element_blank())