Printing Venn Diagram after calculating overlap - r

I'm trying to use the calculate.overlap function within the VennDiagram package to first calculate and then print a Venn Diagram. I was able to calculate the overlap of my data set but looking for help how to print the Venn graphic. Can anyone provide assistance? I read through the documentation but didn't find this.
> library('VennDiagram')
# A simple single-set diagram
cardiome <- letters[1:10]
superset <- letters[8:24]
overlap <- calculate.overlap(
x = list(
"Cardiome" = cardiome,
"SuperSet" = superset
)
);

Another simple example that shows how to print a Venn diagram using the VennDiagram package:
library(VennDiagram)
cardiome <- letters[1:10]
superset <- letters[8:24]
overlap <- calculate.overlap(
x <- list("Cardiome"=cardiome, "SuperSet"=superset))
venn.plot <- draw.pairwise.venn(
area1 = length(cardiome),
area2 = length(superset),
cross.area = length(overlap),
category = c("Cardiome", "Superset"),
fill = c("blue", "red"),
lty = "blank",
cex = 2,
cat.cex = 2,
cat.pos = c(180, 180),
cat.dist = 0.05,
cat.just = list(c(0, 1), c(1, 1))
)
grid.draw(venn.plot)
savePlot(filename="venndiag", type="png")
Venn diagrams with item labels inside the sets:
library(RAM)
vectors <- list(Cardiome=cardiome, Superset=superset)
group.venn(vectors=vectors, label=TRUE,
fill = c("blue", "red"),
cat.pos = c(180, 180),
lab.cex=1.1)

The funtion venn.diagram() does it. For instance in your example
venn.diagram(x = list(
"Cardiome" = cardiome,
"SuperSet" = superset
), "plot_venn")
It saves to working directory. Type getwd() to see what it is set to.
See the
?venn.diagram()
for more info.

?venn.diagram suggests this
library('VennDiagram')
venn.plot <- venn.diagram(
x = list(
cardiome = letters[1:10],
superset = letters[8:24]
),
filename = NULL
);
grid.draw(venn.plot);

Related

Outputting a list of the intersecting genes/Values when making a VennDiagram in R with the VennDiagram package

I made a VennDiagram with five intersecting vectors, each containing a set of gene names.
Does anyone know whether I can somehow export the list of genes, which overlap in the different intersections?
I know I can do that with several online tools, such as Venny or InteractiVenn, but it would be much more convenient in R.
This is the code I use:
venn.diagram(
x = list(set1, set2, set3, set4, set5),
category.names = c("set1", "set2", "set3", "set4", "set5"),
filename= "my_path/venn.png",
output=NULL,
# # Output features
imagetype="png" ,
height = 2000 ,
width = 2000 ,
units = "px",
na = 'stop',
resolution = 300,
compression = "lzw",
lwd = 2,
col = c("#1ABC9C", "#85C1E9", "#CD6155", "#5B2C6F", "#F8C471"),
cat.col = c("#1ABC9C", "#85C1E9", "#CD6155", "#5B2C6F", "#F8C471"),
fill = c(alpha("#1ABC9C",0.3), alpha("#85C1E9",0.3), alpha("#CD6155",0.3), alpha("#5B2C6F",0.3), alpha("#F8C471",0.3)),
cex = 1.5,
fontfamily = "sans",
cat.cex = 1.15,
cat.default.pos = "text",
cat.fontfamily = "sans",
cat.dist= c(0.055),
cat.pos= c(1)
)
Thanks!
I suspect the OP has moved on, but I had the same question.
Here's what I came up with for a five set example- NB this uses a different package:
require(nVennR)
require(dplyr)
# wrangle input
Venn <- plotVenn(list("set1"=set1, "set2"=set2, "set3"=set3, "set4"=set4,
"set5"=set5), outFile = "DataSourceVenn.svg") # produces associated diagram
# generate lists of each intersect
intersects <- listVennRegions(Venn)
# pull lists together
intersects <- plyr::ldply(intersects, cbind)
# insert own appropriate col name for V1
colnames(intersects)<-c('Intersect','V1')
# transpose data into columns for each intersect
intersects <- dcast(setDT(intersects), rowid(Intersect) ~ Intersect, value.var =
"V1")[,Intersect:=NULL]

plot(var()) displays two different plots, how do I merge them into one? Also having two y axis

> dput(head(inputData))
structure(list(Date = c("2018:07:00", "2018:06:00", "2018:05:00",
"2018:04:00", "2018:03:00", "2018:02:00"), IIP = c(125.8, 127.5,
129.7, 122.6, 140.3, 127.4), CPI = c(139.8, 138.5, 137.8, 137.1,
136.5, 136.4), `Term Spread` = c(1.580025, 1.89438, 2.020112,
1.899074, 1.470544, 1.776862), RealMoney = c(142713.9916, 140728.6495,
140032.2762, 139845.5215, 139816.4682, 139625.865), NSE50 = c(10991.15682,
10742.97381, 10664.44773, 10472.93333, 10232.61842, 10533.10526
), CallMoneyRate = c(6.161175, 6.10112, 5.912088, 5.902226, 5.949956,
5.925538), STCreditSpread = c(-0.4977, -0.3619, 0.4923, 0.1592,
0.3819, -0.1363)), row.names = c(NA, -6L), class = c("tbl_df",
"tbl", "data.frame"))
I want to make my autoregressive plot like this plot:
#------> importing all libraries
library(readr)
install.packages("lubridtae")
library("lubridate")
install.packages("forecast")
library('ggplot2')
library('fpp')
library('forecast')
library('tseries')
#--------->reading data
inputData <- read_csv("C:/Users/sanat/Downloads/exercise_1.csv")
#--------->calculating the lag=1 for NSE50
diff_NSE50<-(diff(inputData$NSE50, lag = 1, differences = 1)/lag(inputData$NSE50))
diff_RealM2<-(diff(inputData$RealMoney, lag = 1, differences = 1)/lag(inputData$RealMoney))
plot.ts(diff_NSE50)
#--------->
lm_fit = dynlm(IIP ~ CallMoneyRate + STCreditSpread + diff_NSE50 + diff_RealM2, data = inputData)
summary(lm_fit)
#--------->
inputData_ts = ts(inputData, frequency = 12, start = 2012)
#--------->area of my doubt is here
VAR_data <- window(ts.union(ts(inputData$IIP), ts(inputData$CallMoneyRate)))
VAR_est <- VAR(y = VAR_data, p = 12)
plot(VAR_est)
I want to my plots to get plotted together in same plot. How do I serparate the var() plots to two separate ones.
Current plot:
My dataset :
dataset
Okay, so this still needs some work, but it should set the right framework for you. I would look more into working with the ggplot2 for future.
Few extra packages needed, namely library(vars) and library(dynlm).
Starting from,
VAR_est <- VAR(y = VAR_data, p = 12)
Now we extract the values we want from the VAR_est object.
y <- as.numeric(VAR_est$y[,1])
z <- as.numeric(VAR_est$y[,2])
x <- 1:length(y)
## second data set on a very different scale
par(mar = c(5, 4, 4, 4) + 0.3) # Leave space for z axis
plot(x, y, type = "l") # first plot
par(new = TRUE)
plot(x, z, type = "l", axes = FALSE, bty = "n", xlab = "", ylab = "")
axis(side=4, at = pretty(range(z)))
mtext("z", side=4, line=3)
I will leave you to add the dotted lines on etc...
Hint: Decompose the VAR_est object, for example, VAR_est$datamat, then see which bit of data corresponds to the part of the plot you want.
Used some of this

R igraph Format Date on axis

In the following igraph there are dates to be plotted as marks on the x-axis. Below I provided an example. As the dates are specified in the label matrix they are formatted into an atomic value. How do I get the dates on the x-axis to be displayed in a regular date format?
library(igraph)
nodes=data.frame(
c(0,1,2,3),
c("A","B","C","D")
)
colnames(nodes) = c("id","name")
links = data.frame(
c(0,0,1,2),
c(1,2,3,3)
)
colnames(links) = c("from","to")
layout = matrix(
c(as.Date('2010-01-01'),1, as.Date('2010-01-02'),1, as.Date('2010-01-02'),2, as.Date('2010-01-06'),1), byrow = TRUE, nrow=4
)
net = graph.data.frame(links, vertices = nodes)
plot.igraph(
net, xaxt="n",layout=layout,axes=TRUE,asp=0, rescale=FALSE,xlim=c(as.Date('2010-01-01'),as.Date('2010-01-06')),ylim=c(1,2)
)
You can replace the axis by your own values as explained here.
Using your code, it gives:
layout <- data.frame(Date = as.Date(c('2010-01-01','2010-01-02','2010-01-02','2010-01-06')), value = c(1,2,1,1))
plot.igraph(
net,
layout = layout,
rescale = FALSE,
axis = FALSE,
asp = 0,
xlim = as.Date(c('2010-01-01', '2010-01-06')),
ylim = c(1,2)
)
axis(1, at = as.numeric(layout$Date), labels = layout$Date, cex.axis = 0.9)
axis(2, at = 1:max(layout$value), labels = 1:max(layout$value))

plotly Sankey diagram: Can I make 4 or more links between two nodes?

I created a Sankey diagram using the plotly package.
Please look at below example. I tried to make five streams, 1_6_7, 2_6_7, and so on. But two of five links between 6 and 7 disappeared. As far as I see, plotly allows to make only three or less links between two nodes.
Can I remove this restrictions ? Any help would be greatly appreciated.
Here is an example code and the outputs:
d <- expand.grid(1:5, 6, 7)
node_label <- 1:max(d)
node_colour <- scales::alpha(RColorBrewer::brewer.pal(7, "Set2"), 0.8)
link_source_nodeind <- c(d[,1], d[,2]) - 1
link_target_nodeind <- c(d[,2], d[,3]) - 1
link_value <- rep(100, nrow(d) * 2)
link_label <- rep(paste(d[,1], d[,2], d[,3], sep = "_"), 2)
link_colour <- rep(scales::alpha(RColorBrewer::brewer.pal(5, "Set2"), 0.2), 2)
p <- plotly::plot_ly(type = "sankey",
domain = c(x = c(0,1), y = c(0,1)),
orientation = "h",
node = list(label = node_label,
color = node_colour),
link = list(source = link_source_nodeind,
target = link_target_nodeind,
value = link_value,
label = link_label,
color = link_colour))
p

turn off grid lines for R xyplot timeseries

I am plotting a time series with the timePlot function of the open air package of R. The graph has grey grid lines in the background that I would like to turn off but I do not find a way to do it. I would expect something simple such as grid = FALSE, but that is not the case. It appears to be rather complex, requiring the use of extra arguments which are passed to xyplot of the library lattice. I believe the answer lies some where in the par.settings function but all attempts have failed. Does anyone have any suggestions to this issue?
Here is by script:
timeozone <- import(i, date="date", date.format = "%m/%d/%Y", header=TRUE, na.strings="")
ROMO = timePlot(timeozone, pollutant = c("C7", "C9", "C10"), group = TRUE, stack = FALSE,y.relation = "same", date.breaks = 9, lty = c(1,2,3), lwd = c(2, 3, 3), fontsize = 15, cols = c("black", "black"), ylab = "Ozone (ppbv)")
panel = function(x, y) {
panel.grid(h = 0, v = 0)
panel.xyplot(x,y)
}

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