I am trying to label the data points which are shaded in the plot.
Here is my sample data :
genes logFC PValue
1 Arhgap8 -5.492152 2.479473e-99
2 Asns -2.519970 2.731718e-93
3 Bmp4 -1.663583 4.767201e-72
4 Casp1 -1.650139 2.212689e-25
5 Ctgf -1.272772 1.000103e-61
6 Eya4 -2.328052 2.077364e-68
my plot code till now :
plot(sample$logFC,-log10(as.numeric(sample$PValue)),pch = 20,xlab = 'Log2 FoldChange',ylab = '-Log10 p-value',col = 'blue',xlim = c(-10,8),ylim = c(0,300),cex.lab=1.5, cex.axis=1.5)
points(sample$logFC,-log10(as.numeric(sample$PValue)),col = "dark green")
with(subset(sample,genes=='Arhgap8'),points(logFC,-log10(as.numeric(PValue)),pch = 20, col="orange"))
I have tried using the below command including text;but it doesnt show me the label.
with(subset(sample,genes=='Arhgap8'),points(logFC,-log10(as.numeric(PValue)),pch = 20, col="violet"),text(sample,labels = sample$genes,cex = 0.9,pos = 4))
The correct way to use with to run to commands would be
with(subset(sample, genes=='Arhgap8'), {
points(logFC, -log10(as.numeric(PValue)), pch = 20, col="violet")
text(logFC, -log10(as.numeric(PValue)), labels = genes, cex = 0.9, pos = 4)
})
When you pass more arguments with with(), they are silently ignored. For example
with(iris, mean(Sepal.Length), stop("not run"))
Related
I am generating a landscape pattern that evolves over time. The problem with the code is that I have clearly defined a window for the object bringing up the error but the window is not being recognised. I also do not see how any points are falling outside of the window, or how that would make a difference.
library(spatstat)
library(dplyr)
# Define the window
win <- owin(c(0, 100), c(0, 100))
# Define the point cluster
cluster1 <- rMatClust(kappa = 0.0005, scale = 0.1, mu = 20,
win = win, center = c(5,5))
# define the spread of the points
spread_rate <- 1
new_nests_per_year<-5
years<-10
# Plot the initial cluster
plot(win, main = "Initial cluster")
points(cluster1, pch = 20, col = "red")
newpoints<-list()
# Loop for n years
for (i in 1:years) {
# Generate new points that spread from the cluster
newpoints[[1]] <-rnorm(new_nests_per_year, mean = centroid.owin(cluster1)$y, sd = spread_rate)
newpoints[[2]] <-rnorm(new_nests_per_year, mean = centroid.owin(cluster1)$x, sd = spread_rate)
# Convert the list to a data frame
newpoints_df <- data.frame(newpoints)
# Rename the columns of the data frame
colnames(newpoints_df) <- c("x", "y")
# Combine the new points with the existing points
cluster1_df <- data.frame(cluster1)
newtotaldf<-bind_rows(cluster1_df,newpoints_df)
cluster1<-as.ppp(newtotaldf, x = newtotaldf$x, y = newtotaldf$y,
window = win)
# Plot the updated cluster
plot(win, main = paste("Cluster after year", i))
points(cluster1, pch = 20, col = "red")
}
However, when I run line:
cluster1<-as.ppp(newtotaldf, x = newtotaldf$x, y = newtotaldf$y,
window = win)
I recieve the error:
Error: x,y coords given but no window specified
Why would this be the case?
In your code, if you use the command W = win it should solve the issue. I also believe you can simplify the command without specifying x and y:
## ...[previous code]...
cluster1 <- as.ppp(newtotaldf, W = win)
plot(win)
points(cluster1, pch = 20, col = "red")
I am a newer in R. I would like to create a circular heatmap and set some split according to https://jokergoo.github.io/2020/05/21/make-circular-heatmaps/, which says :
If the value for split argument is a factor, the order of the factor levels controls the order of heatmaps. If split is a simple vector, the order of heatmaps is unique(split).
# note since circos.clear() was called in the previous plot,
# now the layout starts from theta = 0 (the first sector is 'e')
circos.heatmap(mat1, split = factor(split, levels = c("e", "d", "c", "b", "a")),
col = col_fun1, show.sector.labels = TRUE)
refered result plot
my data was like this:
esters.csv
This is my code
library(circlize)
library(ComplexHeatmap)
library(dendextend)
mat1=read.csv("esters.csv")
row.names(mat1)<-mat1[,1]#
mat2<-mat1[,-1]##remove the first column
mat3<-mat1[-1,]##remove the first row
#Draw circoheatmap
col_fun1 = colorRamp2(c(0, 0.00001, 0.0001, 0.001, 0.01,0.1, 0.4, 0.8), c("#FAFAFA", "#EAF7E7", "#E0F3DC", "#D7F0D1", "#CDEBC6", "#D5E4FD", "#8CACE3", "#5E7192"))##
circos.par(start.degree = 90, gap.degree = 10, gap.after = c(10))##
mat1 = mat1[sample(165, 165), ] # randomly permute rows
split = sample(letters[1:5], 165, replace = TRUE)
splits = factor(split, levels = letters[1:5])
circos.heatmap(mat2, col = col_fun1, split = splits,
dend.track.height = 0.15,
dend.side = "inside",
rownames.side = "outside",
dend.callback = function(dend, m, si) {
color_branches(dend, k = 4, col = 1:4)
}
)
#By default, the numeric matrix is clustered on rows.
#Used to draw legend
lgd = Legend(title = "Relative abundance", col_fun = col_fun1)
grid.draw(lgd)
circos.clear()
I want to add the split according to the specific row name, like "ester40", "ester80", "ester128". For example, the first split or sector contained 40 rows named "ester1, ester2, ester3, ester4,...to ester40" and all columns from "H6d_T" to "M10d_P".
I tried my best to understand it, but it still did not work.
Did anyone could tell me what should I type in
split = ???
The scatterplot3D function seems to be plotting incorrectly and I am unsure about why. For example, the following commands should yield identical plots but they do not. I also providing reproducible code to create the data structures below. I guess it is not correctly processing my input?
install.packages("scatterplot3d")
library("scatterplot3d")
cent = array(dim=c(4,3))
cll = c("Factor1", "Factor2", "Factor3")
colnames(cent) = cll
cent[1,] = c(-0.25320707, -0.5878291, -0.4522262)
cent[2,] = c(2.49368231, 0.5911989, -0.3728652)
cent[3,] = c(-0.02927063, -0.2627355, 1.6147719)
cent[4,] = c(-0.63391974, 1.0109955, -0.1542808)
new.cent = array(dim=c(4,3))
colnames(new.cent) = cll
new.cent[1,] = c(2.1572533, 0.4985594, -0.1989068)
new.cent[2,] = c(-0.1362396, -0.4134629, 1.2677813)
new.cent[3,] = c(-0.2566698, -0.6602819, -0.5245323)
new.cent[4,] = c(-0.5847768, 0.7672588, -0.1918044)
Now I try to plot
plot.new()
scatterplot3d(new.cent, pch = 10)
points(cent, pch = 3)
plot of new.cent with cent added as points in different format
plot.new()
scatterplot3d(cent, pch = 3)
points(new.cent, pch = 10)
plot of cent with new.cent added as points in different format
The above points don't seem correct in any case... Moreover, if I try to add a single point as in "points(cent[1,])" it adds three points which is also indicative of the malfunction.
Please refer to linked manual, how to add points3d to the plot. Also, to compare plots, please make sure they axes limits are the same.
library("scatterplot3d")
cent = array(dim=c(4,3))
cll = c("Factor1", "Factor2", "Factor3")
colnames(cent) = cll
cent[1,] = c(-0.25320707, -0.5878291, -0.4522262)
cent[2,] = c(2.49368231, 0.5911989, -0.3728652)
cent[3,] = c(-0.02927063, -0.2627355, 1.6147719)
cent[4,] = c(-0.63391974, 1.0109955, -0.1542808)
new.cent = array(dim=c(4,3))
colnames(new.cent) = cll
new.cent[1,] = c(2.1572533, 0.4985594, -0.1989068)
new.cent[2,] = c(-0.1362396, -0.4134629, 1.2677813)
new.cent[3,] = c(-0.2566698, -0.6602819, -0.5245323)
new.cent[4,] = c(-0.5847768, 0.7672588, -0.1918044)
plot.new()
a <- scatterplot3d(new.cent, pch = 10, xlim = c(-1,2.5), ylim = c(-1,1.5), zlim = c(-1,2))
a$points3d(cent, pch = 3)
b <- scatterplot3d(cent, pch = 3, xlim = c(-1,2.5), ylim = c(-1,1.5), zlim = c(-1,2))
b$points3d(new.cent, pch = 10)
Created on 2022-01-27 by the reprex package (v2.0.1)
I am trying to create an heatmap with a row annotation inclusive of p-values as reported in the example in the guide for the use of the ComplexHeatmap package (https://jokergoo.github.io/ComplexHeatmap-reference/book/heatmap-annotations.html#simple-annotation).
I tried to reproduce the example:
library(ComplexHeatmap)
library(circlize) # colorRamp2 function
set.seed(123)
pvalue = 10^-runif(10, min = 0, max = 3)
is_sig = pvalue < 0.01
pch = rep("*", 10)
pch[!is_sig] = NA
# color mapping for -log10(pvalue)
pvalue_col_fun = colorRamp2(c(0, 2, 3), c("green", "white", "red"))
ha = HeatmapAnnotation(
pvalue = anno_simple(-log10(pvalue), col = pvalue_col_fun, pch = pch),
annotation_name_side = "left")
ht = Heatmap(matrix(rnorm(100), 10), name = "mat", top_annotation = ha)
# now we generate two legends, one for the p-value
# see how we define the legend for pvalue
lgd_pvalue = Legend(title = "p-value", col = pvalue_col_fun, at = c(0, 1, 2, 3),
labels = c("1", "0.1", "0.01", "0.001"))
# and one for the significant p-values
lgd_sig = Legend(pch = "*", type = "points", labels = "< 0.01")
# these two self-defined legends are added to the plot by `annotation_legend_list`
draw(ht, annotation_legend_list = list(lgd_pvalue, lgd_sig))
but when I am creating the annotation ha I get the error
Error in anno_simple(-log10(pvalue), col = pvalue_col_fun, pch = pch) :
could not find function "anno_simple"
likely showing a possible problem with the package.
The version of the ComplexHeatmap package I am running is 1.20.0.
The R version is 3.5.1.
Could you please help me solving this problem?
Thanks
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]