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StatFastaFiles.R
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StatFastaFiles.R
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########################################################################################
## This file is a part of YAP package of scripts. https://github.com/shpakoo/YAP
## Distributed under the MIT license: http://www.opensource.org/licenses/mit-license.php
## Copyright (c) 2011-2013 Sebastian Szpakowski
########################################################################################
library(Biostrings)
library(ggplot2)
library(grid)
library(scales)
multiplot <- function(..., plotlist=NULL, cols=1, layout=NULL)
{
require(grid)
# Make a list from the ... arguments and plotlist
plots <- c(list(...), plotlist)
numPlots = length(plots)
# If layout is NULL, then use 'cols' to determine layout
if (is.null(layout))
{
layout = grid.layout(ceiling(numPlots/cols), cols)
}
# create a panel that will be used to map ids later
panel = matrix(1:(layout$nrow * layout$ncol), nrow = layout$nrow, ncol = layout$ncol, byrow=TRUE )
if (numPlots==1)
{
print(plots[[1]])
}
else
{
# Set up the page
grid.newpage()
pushViewport(viewport(layout = layout))
for (i in 1:numPlots)
{
matching <- as.data.frame(which(panel == i, arr.ind = TRUE))
print ( plots[[i]], vp = viewport( layout.pos.row = matching$row,
layout.pos.col = matching$col)
)
}
}
}
histopanel = function(stat, filename, xlab, xlim, color, extension)
{
par(mar =c(0,4,3,2))
boxplot(stat, horizontal=TRUE, ylim=xlim, ylim = c(0,1), lwd=1, main="", ylab="", col=color, axes=FALSE, xlim=c(0.8, 1.2), outline=F)
labs = c(median(stat), quantile(stat, c(0.25, 0.75)))
axis(1, at=labs, lab = round(labs,1) , las=2)
par(mar =c(5,4,4,2))
hist(stat,main="", xlab=xlab, col=color, xlim=xlim, br=seq(xlim[1]-extension, xlim[2]+extension, length.out=150), axes=FALSE, ylab=paste("frequency"))
labs = seq(min(stat), max(stat), length.out=10)
axis(1, at = labs, lab=round(labs,1), las=0)
axis(2)
box()
}
makePlot = function(fastafile, fastas=list(), main="Fasta", prefix="",...)
{
layout( matrix(c(1,2,3,4), 2, 2, byrow = FALSE), heights=c(0.1, 0.9), widths=c(0.15, 0.85))
cols = c("blue", "lightblue", "red", "green", "seagreen", "lightgreen", "tomato1", "violetred")
random= round(runif(1, min=1, max=length(cols)),0)
if (length(fastas)==0)
{
#fastas= readFASTA(fastafile, strip.descs=TRUE)
fastas = readDNAStringSet(fastafile, use.names=FALSE)
lengths = width(fastas)
freqs = alphabetFrequency(fastas, baseOnly=TRUE)
actualchars = apply(alphabetFrequency(fastas, baseOnly=TRUE, collapse=FALSE)[,1:4],1,sum)
}
else
{
lengths = fastas$lengths
actualchars = fastas$actualchars
}
stat= log10(lengths)
desc = "sequence lengths"
xlim=c(min(stat),max(stat))
histopanel(stat, fastafile, desc, xlim, cols[random], 20)
#~ stat= log10(lengths)
#~ desc = "log 10 of sequence length"
#~ xlim=c(min(stat),max(stat))
#~ histopanel(stat, fastafile, desc, xlim, cols[random], log10(20))
stat = log10(actualchars)
desc = "lengths excluding excluding ,.-"
xlim=c(min(stat),max(stat))
histopanel(stat, fastafile, desc, xlim, cols[random], 20)
mtext(paste("Distribution of fragment sizes in\n", main, "\nn=", length(stat), sep=""), outer=TRUE, side=3, line=-5)
return (list(lengths=lengths, actualchars=actualchars))
}
makeGGplot=function(fastafiles, fastas=list(), main=fastafile, prefix="",...)
{
global = data.frame()
for (f in fastafiles)
{
fastas = readDNAStringSet(f, use.names=FALSE)
lengths = width(fastas)
freqs = as.data.frame(alphabetFrequency(fastas, baseOnly=TRUE))
actualchars = apply(alphabetFrequency(fastas, baseOnly=TRUE, collapse=FALSE)[,1:4],1,sum)
alldata = cbind(freqs, actualchars, lengths)
alldata$gcrelative = (alldata$C + alldata$G) / (alldata$A + alldata$C + alldata$G + alldata$T)
alldata$sizecat=as.character(floor(log10(actualchars)))
a = strsplit( f, "\\.")[[1]]
if (length(a)>2)
{
a = a[2]
b = strsplit( a,"-")[[1]]
if (length(b)>2)
{
b=b[1]
}
else
{
b=f
}
}
else
{
b=f
}
cat(f, "->", a, "->", b, "\n")
alldata$file=rep(b, nrow(alldata))
if (nrow(global)==0)
{
global=alldata
}
else
{
global=rbind(alldata,global)
}
}
#maintitle = paste("Distribution of sequence sizes in\n", main, "\n(n=", length(lengths),")", sep="")
A = (ggplot(global, aes(file, lengths, color=file))
+ geom_boxplot()
+ scale_y_log10(breaks = trans_breaks("log10", function(x) 10^x),
labels = trans_format("log10", math_format(10^.x)))
+ coord_flip()
+ theme(axis.ticks = element_blank(), axis.text.y = element_blank())
)
B = (ggplot(global, aes(sizecat , (C + G) / (A + C + G + T), color=file ))
+ geom_jitter(alpha = I(1/100))
+ geom_boxplot()
#+ scale_x_discrete(labels=math_format( "[", 10^.x , 10^.x+1, ")") )
+ scale_x_discrete(labels=math_format( expr=paste("[",10^.x, ",", 10^(.x+1), ")" )))
)
C1 = (ggplot(global, aes(lengths, ..count.., fill=file, group=file ))
+ stat_bin(aes(y=..count..), geom="area", position="stack", weight=2)
+ scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
labels = trans_format("log10", math_format(10^.x)))
)
C2 = (ggplot(global, aes(lengths, ..count.., fill=file, group=file ))
+ stat_bin(aes(y=..count..), geom="area", position="dodge", alpha=0.5, weight=2)
+ scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
labels = trans_format("log10", math_format(10^.x)))
)
# C1 = (ggplot(global, aes(lengths, ..count.., fill=file, group=file ))
# + geom_bar(position="stack")
# + scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
# labels = trans_format("log10", math_format(10^.x)))
# )
#
# C2 = (ggplot(global, aes(lengths, ..density.., fill=file, group=file ))
# + geom_bar(position="stack")
# + scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
# labels = trans_format("log10", math_format(10^.x)))
# )
#
# D1 = (ggplot(global, aes(lengths, ..count.., fill=file ))
# + geom_bar(position = "dodge")
# + scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
# labels = trans_format("log10", math_format(10^.x)))
# )
#
# D2 = (ggplot(global, aes(lengths, ..density.., fill=file ))
# + geom_bar( position= "dodge")
# + scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
# labels = trans_format("log10", math_format(10^.x)))
# )
#
# E1 = (ggplot(global, aes(lengths, fill=file ))
# + stat_bin(aes (ymax = ..count.. ))
# )
# D1 = (ggplot(global, aes(lengths , fill=file ))
# + geom_bar(position="dodge")
# + scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
# labels = trans_format("log10", math_format(10^.x)))
# )
#
# D2 = (ggplot(global, aes(lengths, ..density.. , fill=file ))
# + geom_bar(position="dodge")
# + geom_density(alpha=0.5, weight=2)
# + scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
# labels = trans_format("log10", math_format(10^.x)))
# )
#
#
F = (ggplot(global, aes(lengths, fill=file, group=file ))
+ geom_bar(position="fill")
+ scale_x_log10(breaks = trans_breaks("log10", function(x) 10^x),
labels = trans_format("log10", math_format(10^.x)))
)
#pdf("test.pdf", width=10, height = 15)
png("FastaFileStats_GG.png", width=10, height = 30, units="in", res=250)
multiplot(A, B, C1, C2, F, ncol=1)
dev.off()
invisible(alldata)
}
files = dir(pattern=glob2rx("*.muscle"))
files = append(files, dir(pattern=glob2rx("*.fa")))
files = append(files, dir(pattern=glob2rx("*.align")))
files = append(files, dir(pattern=glob2rx("*.fasta")))
pdf(paste("FastaFileStats_indi.pdf", sep=""), width = 20, height = 8)
L = c()
A = c()
for (f in files)
{
print (f)
x = makePlot(f, main=f)
L = append(L, x$lengths)
A = append(A, x$actualchars)
}
dev.off()
pdf(paste("FastaFileStats_comb.pdf", sep=""), width = 20, height = 8)
makePlot("", fastas=list(lengths=L, actualchars=A), main=paste("combined ", length(files)," files", sep=""))
dev.off()
makeGGplot(files)