filter <- df[apply(df[, -1], MARGIN = 1, function(x) any(x > 0)), ]
write.table(filter, file = "isoforms.nozeros.counts.matrix", sep = "\t", row.names=TRUE, col.names=NA, quote=FALSE)
filter$ad1t06 <- as.numeric(filter$ad1t06)
filter$ad1t06 <- as.numeric(filter$ad1t06)
head(as.numeric(filter$ad1t06))
View(filter)
head(as.numeric(filter$ad1t6))
library("vegan", lib.loc="/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
detach("package:vegan", unload=TRUE)
install.packages("vegan")
install.packages("vegan")
library("vegan", lib.loc="/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
detach("package:permute", unload=TRUE)
library("permute", lib.loc="/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
install.packages("permute")
install.packages("permute")
install.packages("lattice")
install.packages(c("DBI", "digest", "dplyr", "futile.logger", "lambda.r", "lazyeval", "Matrix", "mgcv", "plyr", "R6", "Rcpp", "RcppArmadillo", "stringr", "survival"))
detach("package:datasets", unload=TRUE)
detach("package:graphics", unload=TRUE)
detach("package:grDevices", unload=TRUE)
detach("package:methods", unload=TRUE)
detach("package:stats", unload=TRUE)
detach("package:utils", unload=TRUE)
install.packages(zoo)
install.packages("zoo")
library("zoo", lib.loc="/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
setwd("/Users/alouyakis/Desktop/")
read.csv("rtest.txt")
rtest <- read.delim("~/Desktop/rtest.txt", header=FALSE)
View(rtest)
f<-na.fill(rtest,c(rtest$V1,""))
f
rtest
f<-na.fill(rtest$V2,c(rtest$V2, ""))
f
f<-na.fill(rtest$V2,c("", rtest$V2))
f
library("NOISeq", lib.loc="/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
install.packages(c("ape", "chron", "DBI", "jsonlite", "mgcv", "nlme", "RcppArmadillo", "stringr"))
library("ggplot2", lib.loc="/Library/Frameworks/R.framework/Versions/3.2/Resources/library")
oct_t12 <- read.delim("/Users/alouyakis/Documents/SLSL/metatranscriptome/align_forwards/oct_t12.isoforms.counts.nozeros", row.names=1)
xlabel<-expression("od2t12")
ylabel<-expression("od312")
oct_t12 <- read.delim("/Users/alouyakis/Documents/SLSL/metatranscriptome/align_forwards/oct_t12.isoforms.counts.nozeros", row.names=1)
xlabel<-expression("od2t12")
ylabel<-expression("od312")
xy_oct_t12<-qplot(oct_t12$od2t12, oct_t12$od3t12, data=oct_t12, shape=sample, color=feature, size=I(2), xlab=xlabel, ylab=ylabel) + scale_shape_manual(values = c(17,15,8))
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t3<-theme(axis.line.x = element_line(color="black", size = 1), axis.line.y = element_line(color="black", size = 1), axis.text = element_text(face="bold", color = "black", size=12))
t4<-theme(legend.text = element_text(face="bold", color="black", size=10), legend.position=c(0,1), legend.box.just="left", legend.justification=c(0,1), legend.key.size=unit(0.4,"cm"))
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4)
xy_oct_t12_plot
xy_oct_t12
xy_oct_t12<-qplot(oct_t12$od2t12, oct_t12$od3t12, data=oct_t12, size=I(2), xlab=xlabel, ylab=ylabel) + scale_shape_manual(values = c(17,15,8))
xy_oct_t12
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t3<-theme(axis.line.x = element_line(color="black", size = 1), axis.line.y = element_line(color="black", size = 1), axis.text = element_text(face="bold", color = "black", size=12))
t4<-theme(legend.text = element_text(face="bold", color="black", size=10), legend.position=c(0,1), legend.box.just="left", legend.justification=c(0,1), legend.key.size=unit(0.4,"cm"))
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4)
xy_oct_t12_plot
library(calibrate)
install.packages("calibrate")
library(calibrate)
isoform_labels<-with(subset(oct_t12, od2t12<50000), textxy(od2t12, od3t12, labs=isoform_id, cex=.8))
isoform_labels<-with(subset(oct_t12, od2t12<50000), textxy(od2t12, od3t12, labs=oct_t12$isoform_id, cex=.8))
xy_oct_t12<-qplot(oct_t12$od2t12, oct_t12$od3t12, data=oct_t12, size=I(2), xlab=xlabel, ylab=ylabel) + scale_shape_manual(values = c(17,15,8))
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t3<-theme(axis.line.x = element_line(color="black", size = 1), axis.line.y = element_line(color="black", size = 1), axis.text = element_text(face="bold", color = "black", size=12))
t4<-theme(legend.text = element_text(face="bold", color="black", size=10), legend.position=c(0,1), legend.box.just="left", legend.justification=c(0,1), legend.key.size=unit(0.4,"cm"))
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4+isoform_labels)
xy_oct_t12_plot
ylabel<-expression("od312")
xlabel<-expression("od2t12")
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t3<-theme(axis.line.x = element_line(color="black", size = 1), axis.line.y = element_line(color="black", size = 1), axis.text = element_text(face="bold", color = "black", size=12))
xy_oct_t12_plot
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4+isoform_labels)
xy_oct_t12<-qplot(oct_t12$od2t12, oct_t12$od3t12, data=oct_t12, size=I(2), xlab=xlabel, ylab=ylabel) + scale_shape_manual(values = c(17,15,8))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t4<-theme(legend.text = element_text(face="bold", color="black", size=10), legend.position=c(0,1), legend.box.just="left", legend.justification=c(0,1), legend.key.size=unit(0.4,"cm"))
xlabel<-expression("od2t12")
xlabel<-expression("od2t12")
ylabel<-expression("od312")
xy_oct_t12<-qplot(oct_t12$od2t12, oct_t12$od3t12, data=oct_t12, size=I(2), xlab=xlabel, ylab=ylabel) + scale_shape_manual(values = c(17,15,8))
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t3<-theme(axis.line.x = element_line(color="black", size = 1), axis.line.y = element_line(color="black", size = 1), axis.text = element_text(face="bold", color = "black", size=12))
t4<-theme(legend.text = element_text(face="bold", color="black", size=10), legend.position=c(0,1), legend.box.just="left", legend.justification=c(0,1), legend.key.size=unit(0.4,"cm"))
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4+isoform_labels)
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4)
xy_oct_t12_plot
oct_t12 <- read.delim("/Users/alouyakis/Documents/SLSL/metatranscriptome/align_forwards/oct_t12.isoforms.counts.nozeros", row.names=1)
xlabel<-expression("od2t12")
ylabel<-expression("od312")
xy_oct_t12<-qplot(oct_t12$od2t12, oct_t12$od3t12, data=oct_t12, size=I(2), xlab=xlabel, ylab=ylabel) + scale_shape_manual(values = c(17,15,8))
t1<-theme(plot.background = element_blank(), plot.margin=unit(c(2,4,4,2),"cm"), panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.border = element_blank(), panel.background = element_blank(), axis.line = element_line(size=.4))
t2<-theme(axis.title.x = element_text(face="bold", color="black", size=12), axis.title.y = element_text(face="bold", color="black", size=12), plot.title = element_text(face="bold", color = "black", size=12))
t3<-theme(axis.line.x = element_line(color="black", size = 1), axis.line.y = element_line(color="black", size = 1), axis.text = element_text(face="bold", color = "black", size=12))
t4<-theme(legend.text = element_text(face="bold", color="black", size=10), legend.position=c(0,1), legend.box.just="left", legend.justification=c(0,1), legend.key.size=unit(0.4,"cm"))
xy_oct_t12_plot<-(xy_oct_t12+t1+t2+t3+t4)
xy_oct_t12_plot
View(oct_t12)
plot(cars)
plot(cars)
keggtaxa <- read.delim("dmg_filter8_clean.txt")
library("plyr")
keggtaxa_c <- count(keggtaxa, c(1,2))
write.table(keggtaxa_c, file = "dmg_filter8_count.txt", sep = "\t", row.names=FALSE, col.names=FALSE, quote = FALSE)
detach("package:plyr",unload=TRUE)
head(keggtaxa_c)
View(keggtaxa_c)
View(keggtaxa)
setwd("/Users/alouyakis/Documents/SLSL/dichothrix/20170716_matrix")
keggtaxa <- read.delim("dmg_filter8_genus.txt", header = FALSE)
head(keggtaxa, n = 5)
taxakey <- read.delim("taxa_key_full.txt", header=TRUE)
keggkey <- read.delim("keggkeyL3.txt", header=TRUE)
simple <- merge(keggtaxa, taxakey, by.x = "V2", by.y = "search")
head(simple, n=20)
simple2 <- merge(simple, keggkey, by.x = "V1", by.y = "kegg")
head(simple2, n=20)
order_l3 <- data.frame("order" = simple2$order,
"level3" = simple2$level3)
order_l3 <- data.frame("order" = simple2$order,
"level3" = simple2$level3)
head(simple2, n=20)
tail(simple2, n=20)
order_l3 <- data.frame("order" = simple2$order,
"level3" = simple2$level3)
head(simple2, n=20)
head(simple, n=20)
head(keggkey)
head(simple, n=20)
head(simple2, n=20)
simple2 <- merge(simple, keggkey, by.x = "V1", by.y = "kegg")
head(simple2, n=20)
head(simple, n=20)
colnames(simple)<-c("taxa", "kegg", "taxapath")
head(simple, n=20)
head(keggkey, n=20)
head(simple, n=20)
simple1 <- simple[ grep("unclass", simple$kegg, invert = TRUE, ignore.case = TRUE) , ]
head(simple1)
head(simple2, n=20)
View(simple2)
colnames(simple)<-c("kegg", "taxa", "taxapath", "level3")
colnames(simple2)<-c("kegg", "taxa", "taxapath", "level3")
head(simple2, n=20)
order_l3 <- data.frame("taxapath" = simple2$order,
"level3" = simple2$level3)
order_l3 <- data.frame("taxapath" = simple2$taxapath,
"level3" = simple2$level3)
library("plyr")
keggtaxa_c <- count(order_l3, c(1,2))
head(keggtaxa_c, n=20)
detach("package:plyr",unload=TRUE)
head(keggtaxa_c, n=20)
colnames(keggtaxa_wclass)<-c("taxapath", "level3", "count")
keggtaxa_wclass <- keggtaxa_c[ grep("Unclassified", keggtaxa_c$level3, invert = TRUE, ignore.case = TRUE) , ]
colnames(keggtaxa_wclass)<-c("taxapath", "level3", "count")
library("dplyr")
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_cm, file = "dmg_filter8_matrix_l3_taxapath.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
head(keggtaxa_cm, n = 5)
class(keggtaxa_cm)
library("gplots")
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
keggtaxa_cm <- data.matrix(keggtaxa_cm, rownames.force = TRUE)
keggtaxa_cm[is.na(keggtaxa_cm)] <- 0
heatmap.2(keggtaxa_cm, margins = c(2,20), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
keggtaxa_subset <- keggtaxa_wclass[ grep("Photosynthesis|nitrogen metabolism|sulfur metabolism|Carbon fixation in photosynthetic organisms|Carbon fixation pathways in prokaryotes", keggtaxa_wclass$level3, ignore.case = TRUE) , ]
library("dplyr")
keggtaxa_subset_mat <- reshape(keggtaxa_subset, idvar="order", timevar="level3", direction="wide")
keggtaxa_subset <- keggtaxa_wclass[ grep("Photosynthesis|nitrogen metabolism|sulfur metabolism|Carbon fixation in photosynthetic organisms|Carbon fixation pathways in prokaryotes", keggtaxa_wclass$level3, ignore.case = TRUE) , ]
library("dplyr")
keggtaxa_subset_mat <- reshape(keggtaxa_subset, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_subset_mat, file = "dmg_filter8_matrix_l3_taxapath_subset.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
library("gplots")
rownames(keggtaxa_subset_mat) <- keggtaxa_subset_mat[,1]
keggtaxa_subset_mat[,1] <- NULL
keggtaxa_subset_mat <- data.matrix(keggtaxa_subset_mat, rownames.force = TRUE)
keggtaxa_subset_mat[is.na(keggtaxa_subset_mat)] <- 0
pdf(file = "heatmap_energy.pdf", width = 10, height = 20, useDingbats = FALSE)
heatmap.2(keggtaxa_subset_mat, margins = c(5,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
heatmap.2(keggtaxa_subset_mat, margins = c(5,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
heatmap.2(keggtaxa_subset_mat, margins = c(1,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", keysize = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", keysize = 0.1)
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
colnames(keggtaxa_cm)<-sub("count.","",colnames(keggtaxa_cm))
head(keggtaxa_cm, n = 5)
class(keggtaxa_cm)
keggtaxa_subset <- keggtaxa_wclass[ grep("Photosynthesis|nitrogen metabolism|sulfur metabolism|Carbon fixation in photosynthetic organisms|Carbon fixation pathways in prokaryotes", keggtaxa_wclass$level3, ignore.case = TRUE) , ]
library("dplyr")
keggtaxa_subset_mat <- reshape(keggtaxa_subset, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_subset_mat, file = "dmg_filter8_matrix_l3_taxapath_subset.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
library("gplots")
rownames(keggtaxa_subset_mat) <- keggtaxa_subset_mat[,1]
keggtaxa_subset_mat[,1] <- NULL
keggtaxa_subset_mat <- data.matrix(keggtaxa_subset_mat, rownames.force = TRUE)
keggtaxa_subset_mat[is.na(keggtaxa_subset_mat)] <- 0
pdf(file = "heatmap_energy.pdf", width = 10, height = 20, useDingbats = FALSE)
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
dev.off()
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
library("gplots")
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
colnames(keggtaxa_wclass)<-c("taxapath", "level3", "count")
library("dplyr")
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_cm, file = "dmg_filter8_matrix_l3_taxapath.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
head(keggtaxa_cm, n = 5)
class(keggtaxa_cm)
colnames(keggtaxa_wclass)<-c("taxapath", "level3", "")
library("dplyr")
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_cm, file = "dmg_filter8_matrix_l3_taxapath.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
head(keggtaxa_cm, n = 5)
colnames(keggtaxa_wclass)<-c("taxapath", "level3", "count")
library("dplyr")
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_cm, file = "dmg_filter8_matrix_l3_taxapath.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
head(keggtaxa_cm, n = 5)
class(keggtaxa_cm)
head(keggtaxa_cm, n = 5)
keggtaxa_cmt <- keggtaxa_cm
names(keggtaxa_cmt) <- sub("^(.+[.])([^.]+)$", "\\2", names(keggtaxa_cmt))
head(keggtaxa_cmt, n = 5)
class(keggtaxa_cmt)
names(keggtaxa_cm) <- sub("^(.+[.])([^.]+)$", "\\2", names(keggtaxa_cm))
library("gplots")
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
keggtaxa_cm <- data.matrix(keggtaxa_cm, rownames.force = TRUE)
keggtaxa_cm[is.na(keggtaxa_cm)] <- 0
heatmap.2(keggtaxa_cm, margins = c(2,20), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
keggtaxa_subset <- keggtaxa_wclass[ grep("Photosynthesis|nitrogen metabolism|sulfur metabolism|Carbon fixation in photosynthetic organisms|Carbon fixation pathways in prokaryotes", keggtaxa_wclass$level3, ignore.case = TRUE) , ]
library("dplyr")
keggtaxa_subset_mat <- reshape(keggtaxa_subset, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_subset_mat, file = "dmg_filter8_matrix_l3_taxapath_subset.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
library("gplots")
rownames(keggtaxa_subset_mat) <- keggtaxa_subset_mat[,1]
keggtaxa_subset_mat[,1] <- NULL
keggtaxa_subset_mat <- data.matrix(keggtaxa_subset_mat, rownames.force = TRUE)
keggtaxa_subset_mat[is.na(keggtaxa_subset_mat)] <- 0
pdf(file = "heatmap_energy.pdf", width = 10, height = 20, useDingbats = FALSE)
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
dev.off()
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
keggtaxa_subset_mat <- reshape(keggtaxa_subset, idvar="taxapath", timevar="level3", direction="wide")
names(keggtaxa_subset_mat) <- sub("^(.+[.])([^.]+)$", "\\2", names(keggtaxa_subset_mat))
write.table(keggtaxa_subset_mat, file = "dmg_filter8_matrix_l3_taxapath_subset.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
library("gplots")
rownames(keggtaxa_subset_mat) <- keggtaxa_subset_mat[,1]
keggtaxa_subset_mat[,1] <- NULL
keggtaxa_subset_mat <- data.matrix(keggtaxa_subset_mat, rownames.force = TRUE)
keggtaxa_subset_mat[is.na(keggtaxa_subset_mat)] <- 0
pdf(file = "heatmap_energy.pdf", width = 10, height = 20, useDingbats = FALSE)
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
dev.off()
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(10,5), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(10,10), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(10,20), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(15,20), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(20,20), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(17,20), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(17,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
heatmap.2(keggtaxa_subset_mat, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
pdf(file = "heatmap_energy.pdf", width = 10, height = 20, useDingbats = FALSE)
heatmap.2(keggtaxa_subset_mat, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", cexCol = 1)
dev.off()
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
pdf(file = "heatmap_wlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", key = NULL)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
library("gplots")
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
keggtaxa_cm <- data.matrix(keggtaxa_cm, rownames.force = TRUE)
keggtaxa_cm[is.na(keggtaxa_cm)] <- 0
pdf(file = "heatmap_wlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
pdf(file = "heatmap_woutlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", key = NULL)
dev.off()
library("gplots")
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
keggtaxa_cm <- data.matrix(keggtaxa_cm, rownames.force = TRUE)
keggtaxa_cm[is.na(keggtaxa_cm)] <- 0
pdf(file = "heatmap_wlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
pdf(file = "heatmap_woutlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", key = NULL)
colnames(keggtaxa_wclass)<-c("taxapath", "level3", "count")
library("dplyr")
keggtaxa_cm <- reshape(keggtaxa_wclass, idvar="taxapath", timevar="level3", direction="wide")
write.table(keggtaxa_cm, file = "dmg_filter8_matrix_l3_taxapath.txt", sep = "\t", row.names=FALSE, col.names=TRUE, quote = FALSE)
head(keggtaxa_cm, n = 5)
class(keggtaxa_cm)
names(keggtaxa_cm) <- sub("^(.+[.])([^.]+)$", "\\2", names(keggtaxa_cm))
rownames(keggtaxa_cm) <- keggtaxa_cm[,1]
keggtaxa_cm[,1] <- NULL
keggtaxa_cm <- data.matrix(keggtaxa_cm, rownames.force = TRUE)
keggtaxa_cm[is.na(keggtaxa_cm)] <- 0
library("gplots")
pdf(file = "heatmap_wlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
pdf(file = "heatmap_woutlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", key = NULL)
library("gplots")
pdf(file = "heatmap_wlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none")
dev.off()
pdf(file = "heatmap_woutlegend.pdf", width = 10, height = 40, useDingbats = FALSE)
heatmap.2(keggtaxa_cm, margins = c(19,25), Rowv = "NA", Colv = "NA",
density.info = "none", col ="greenred", trace ="none",
scale = "row", dendrogram = "none", key = FALSE)
dev.off()
setwd("/Users/alouyakis/Documents/SLSL/dichothrix/metaxa2/complete")
fasta <- read.delim("dmg.metaxa2.bacteria.fasta", header=FALSE)
toadd <- read.delim("dmg.metaxa2.taxonomy.txt", header=FALSE)
alldata <- merge(fasta, toadd, by="V1", sort=FALSE, incomparables="")
head(alldata)
head(alldata)
setwd("/Users/alouyakis/Documents/SLSL/dichothrix/metaxa2/complete")
fasta <- read.delim("dmg.metaxa2.bacteria.fasta", header=FALSE)
toadd <- read.delim("dmg.metaxa2.taxonomy.txt", header=FALSE)
alldata <- merge(fasta, toadd, by="V1", sort=FALSE)
head(alldata)
head(fasta)
setwd("/Users/alouyakis/Desktop/")
matrix <- read.delim("nif_counts.txt", header = TRUE)
annot <- read.delim("nit_all.txt", header = TRUE)
full <- merge(matrix, annot, by = "transcript_id")
write.table(full, file="nitrogen_fixation.txt", quote=F, sep="\t", row.names=F)
setwd("/Users/alouyakis/Desktop/")
matrix <- read.delim("nif_matrix.txt", header = TRUE)
annot <- read.delim("nit_all.txt", header = TRUE)
full <- merge(matrix, annot, by = "transcript_id")
write.table(full, file="nitrogen_fixation.txt", quote=F, sep="\t", row.names=F)
setwd("/Users/alouyakis/Desktop/")
matrix <- read.delim("meth_hdr_iso.TPM.not_cross_norm.txt", header = TRUE)
annot <- read.delim("meth_hdr.txt", header = TRUE)
full <- merge(matrix, annot, by = "transcript_id")
write.table(full, file="methanogenesis_hdr.txt", quote=F, sep="\t", row.names=F)
setwd("/Users/alouyakis/Desktop/")
matrix <- read.delim("dsrAB_matrix.txt", header = TRUE)
annot <- read.delim("dsrAB_all.txt", header = TRUE)
full <- merge(matrix, annot, by = "transcript_id")
write.table(full, file="dsrAB.txt", quote=F, sep="\t", row.names=F)
setwd("/Users/alouyakis/Desktop/")
matrix <- read.delim("dsr_matrix.txt", header = TRUE)
annot <- read.delim("dsr_all_genes.txt", header = TRUE)
full <- merge(matrix, annot, by = "transcript_id")
write.table(full, file="dsr.txt", quote=F, sep="\t", row.names=F)
library(VennDiagram)
setwd("/Users/alouyakis/Documents/SLSL/metatranscriptome/gene_kegg_realign/de/noiseqbio/rerun_20170426/20170621/ci95/")
temp = list.files(pattern="*.txt.keggcol")
list2env(
lapply(setNames(temp, make.names(gsub("*.txt.keggcol$", "_k", temp))),
read.delim, header = FALSE), envir = .GlobalEnv)
lapply(ls(pattern = "*_k"), as.vector)
input <- list(deg_up_at18_at06_q95_k, deg_up_mt18_mt06_q95_k, deg_up_ot18_ot06_q95_k)
input <- lapply(as.list(input), function(x) x[x != ""])
names(input) <- c("August", "March", "October")
venn.plot <- venn.diagram(input, "seasons_18v06.tiff",
col = "black",
lwd = 2,
fill = c("red", "green", "cornflowerblue"),
alpha = 0.50,
cex = 2.5,
fontface = "bold",
main.fontfamily = "sans",
sub.fontfamily = "sans",
fontfamily = "sans",
cat.fontfamily = "sans",
cat.col = c("darkred", "darkgreen", "darkblue"),
cat.cex = 0
)
venn.plot <- venn.diagram(input, "seasons_labs_18v06.tiff",
imagetype = "tiff",
height = 3000,
width = 3000,
col = "black",
lwd = 2,
fill = c("red", "green", "cornflowerblue"),
alpha = 0.50,
cex = 2.5,
fontface = "bold",
main.fontfamily = "sans",
sub.fontfamily = "sans",
fontfamily = "sans",
cat.fontfamily = "sans",
cat.cex = 2
)
aug <- deg_up_at12_at24_q95_k[,1]
mar <- deg_up_mt12_mt24_q95_k[,1]
oct <- deg_up_ot12_ot24_q95_k[,1]
intersect_12vs24 <- Reduce(intersect, list(aug, mar, oct))
intersect_12vs24_df <- as.data.frame(intersect_12vs24)
intersect_24vs12_df <- as.data.frame(intersect_24vs12)
intersect_12vs24_df <- as.data.frame(intersect_12vs24)
intersect_24vs12_df <- as.data.frame(intersect_24vs12)
intersect_06vs18_df <- as.data.frame(intersect_06vs18)
intersect_18vs06_df <- as.data.frame(intersect_18vs06)
intersect_12vs24_df <- as.data.frame(intersect_12vs24)
intimes <- list(t06,t12,t18,t24)
intimes <- lapply(as.list(intimes), function(x) x[x != ""])
names(intimes) <- c("06:00","12:00","18:00","00:00")
venn.plot
getwd()
setwd("~/Desktop/mcb5472r/")
library(knitr)
mkdir(output)
dir.create(output)
dir.create("output")
setwd("~/Desktop/mcb5472r/output")