heatmap in R how to resize columns labels? - r

I have a data.matrix that is approximately 4000 rows and 100 columns. I am doing a heatmap of the data like:
data<-heatmap(data_matrix,Rowv=NA,Colv=NA,col=cm.colors(256),scale="column",margins=c(5,10))
But the problem that I got is that the labels that appear in the column are too grouped, so it is impossible to visualize them correctly. How I can resize the heatmap so I can see the values of the labels of the column? I tried to print it in pdf, but it only appears a black stripe.
Thanks
I am including a figure of the heatmap, the portion that I want to see are the labels that are in the right part, but they are too close together.

First of all it's better to put your output directly to a PDF file - you may use other image formats but PDF is the best because it is a vector output and you can zoom as much as you want:
pdf("Your-file.pdf", paper="a4", width=8, height=8)
Then it's better to use pheatmap( = pretty heatmap) package. It makes really better heatmaps with a color key besides your heatmap. Finally although the pheatmap() function tries to reduce the label size while you have many rows, but it fails for really large number of rows. So I use the code below for really high - but not too high - number of rows:
library(pheatmap)
library(gplots)
if (nrow(table) > 100) stop("Too many rows for heatmap, who can read?!")
fontsize_row = 10 - nrow(table) / 15
pheatmap(table, col=greenred(256), main="My Heatmap", cluster_cols=F,
fontsize_row=fontsize_row, border_color=NA)
You may change fontsize_col for the column labels. You have many interesting options like display_numbers to have the values inside the cells of your heatmap. Just read ?pheatmap.
This is an example generated by the default parameters of pheatmap() command:
Finally note that too many rows are easy to read on a display, but useless for print.

In Rstudio you can easily resize the graphic window, same holds for Rgui. Alternatively, if you save the plot to file you can use a bigger size for your graphics, e.g. bigger width and height when calling pdf or png.

You can use cexRow = and cexCol =.
You can get more information into ??heatmap.2
# Row/Column Labeling
margins = c(5, 5),
ColSideColors,
RowSideColors,
cexRow = 0.2 + 1/log10(nr),
cexCol = 0.2 + 1/log10(nc),
labRow = NULL,
labCol = NULL,
srtRow = NULL,
srtCol = NULL,
adjRow = c(0,NA),
adjCol = c(NA,0),
offsetRow = 0.5,
offsetCol = 0.5,
colRow = NULL,
colCol = NULL

If you use pheatmap (https://www.rdocumentation.org/packages/COMPASS/versions/1.10.2/topics/pheatmap) you can spread out those labels by adjusting the cellheight parameter.
If you are doing this in R notebook, even though the entire heat map will not display in your output window when you run the code, when you save the heat map to your computer using the filename parameter, pheatmap will automatically calculate the optimal size for the output file so that your entire heatmap will be displayed in your output file. If this size is not to your liking you can adjust using width and height parameters, but it is unlikely you will want to do this.

Related

How can I re-scale a forest plot in RStudio?

I am trying to reproduce the plot from the example dataset in the robumeta package in R Studio. While the script works (as expected), I can only see a fraction of the graph. When I increase the size of the window, I get to see more but never the whole thing because apparently, my computer screen is too small and there is no option to scroll up or down. Is there a way to re-scale the forest plot or to print it to pdf (with several pages, if needed)?
Here's the code from package description file:
install.packages("robumeta")
library(robumeta)
data(oswald2013.ex1)
oswald_intercept <- robu(formula = effect.size ~ 1, data = oswald2013.ex1, studynum = Study, var.eff.size = var.eff.size, rho = 0.8, small = TRUE)
forest.robu(oswald_intercept, es.lab = "Crit.Cat", study.lab = "Study",
"Effect Size" = effect.size, # optional column
"Weight" = r.weights) # optional column
png(filename, height, width, pointsize)
#your plot code
dev.off()
in which you play around with the height, width, and pointsize parameters should allow you to save the graph to your desired view size. It won't save as a pdf, but rather a png, which should be ok if your goal is just to view the entire forest plot.

R figure being cropped

Here's a bit of a basic question, you'd think R would automate this always. I'm making a heatmap (basic stuff, png() into heatmap.2() into dev.off()), and my row labels get cleaved off on the right hand side, along with a tiny part of the dendrogram on the left:
Fiddling with the margins manually would eventually lead to a sensible output, but the problem is that this is part of an automated pipeline with biologist users in mind. Surely there's some automated way to do this, right? I mean, in RGui on OSX, a quick reshape of the figure window fixes the layout automatically, so it has to be possible. Thanks, and sorry to bother you.
EDIT: Procedure to reproduce this visualisation:
Input data:
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CATMA3A53880,3.917,3.6689,3.7213,3.8812,3.8253,4.4861,4.258,4.7926,4.9737,4.0869,3.2183,3.5812,3.408,3.3128,3.3915,4.1923,3.9122,4.0586,4.2707,4.3077,4.8926,4.1982,3.4817,3.5267,3.6952,3.6632,3.9304,4.0793,3.9499,4.2175,4.8303,4.9599,4.6336,3.8998,3.7932,3.8572,3.2167,3.7749,4.3971,4.0662,3.9241,4.6407,4.2837,4.9644,4.972,4.2565,3.8796,3.383,3.2382,4.1017,4.058,4.0423,3.6033,4.0774,5.141,4.9736,4.4372,3.8969,3.7386,3.3618,3.539,4.2588,3.4726,3.7424,3.5818,4.9159,4.3567,4.1291,4.1108,4.4035,3.1374,3.4675,3.762,3.9264,3.7319,4.1205,2.0915,4.4192,4.5049,4.5427,4.6205,3.4653,3.6017,3.3376,3.266,3.5561,3.4538,3.761,4.2013,4.1787,4.017,4.7773,3.748,4.4977,3.8685,3.7464
CATMA5A09500,6.2838,5.1076,6.6209,5.7153,5.9395,5.3601,4.2366,5.189,3.3074,4.8701,5.0357,5.0951,6.2843,5.691,5.5054,5.9949,5.0834,5.1484,4.5884,4.805,4.458,5.0816,4.7264,5.3661,5.0645,5.8293,5.2877,5.6602,5.3336,4.7329,4.843,5.1901,3.8431,4.683,5.7106,4.0774,6.5689,5.8061,5.3445,5.2905,3.837,4.6271,4.2277,4.6165,4.0081,4.5176,4.259,4.6363,4.8557,3.9828,5.9728,5.4698,5.4102,4.5802,5.0247,4.8967,4.0116,2.6636,5.4684,4.3454,6.6893,6.5624,6.1464,5.4444,5.3309,5.6682,5.5012,4.3162,2.9028,3.3906,4.6684,4.914,5.3601,5.5138,6.2191,5.8043,5.8165,5.1155,3.8681,4.9268,4.0232,6.1699,4.6327,5.7364,6.1934,6.7188,5.0755,5.7058,5.3703,4.3921,3.2108,4.9503,4.1003,4.8225,4.6701,4.7166
CATMA5A12680,1.7891,1.362,1.4303,0.61973,0.54124,1.2733,0.7775,0.66788,1.7338,0.63125,1.5852,0.91616,1.0712,0.81919,0.90152,0.77799,1.0835,0.32735,2.0868,0.5895,1.1445,0.64545,0.71776,0.33929,1.42,1.0729,1.4879,0.86379,0.95453,1.2928,0.97753,1.1738,0.79397,0.31563,0.86345,0.67595,1.3501,1.079,1.2034,1.2432,1.3696,1.1473,0.72528,0.57199,0.85965,0.65339,0.47614,0.43219,1.363,2.4026,0.98947,0.85204,1.2591,2.3151,1.6775,1.6555,1.0371,2.5586,-0.097071,0.91744,1.068,1.6819,1.0122,0.99911,0.75267,1.2195,0.42175,0.2554,0.4819,0.80025,0.44517,0.32442,1.9863,1.5019,1.2893,1.0669,1.6881,1.7581,1.6505,1.943,2.141,1.018,0.68207,0.84392,1.1452,1.009,1.1376,1.0572,1.9258,1.7039,0.10261,1.4549,0.94693,0.77945,0.049658,0.84178
CATMA5A14990,0.41247,0.51378,0.375,-0.24526,0.027658,-0.015345,-0.028278,-0.2643,0.3905,0.12299,0.94334,0.11482,0.50109,-0.55162,0.10768,-0.26433,-0.31064,-0.76526,1.0147,-0.73178,0.3323,-0.13657,-0.14013,-0.17878,0.31259,0.36723,0.55499,-0.2664,0.31862,0.60225,0.078919,0.18282,0.23014,-0.27835,0.16392,0.58131,1.052,0.062394,0.064929,-0.11918,-0.2167,-0.26018,-0.21649,-0.032523,-0.05763,-0.62775,-0.29148,0.13633,0.72715,1.535,0.08501,0.76137,0.54934,1.5163,-0.26612,0.58127,0.30339,1.8464,-0.17161,0.30309,-0.070279,0.28016,-0.036628,0.67464,0.34753,0.26499,-0.17856,-0.61162,-0.17941,-0.01017,0.21112,0.026389,0.64566,-0.39685,0.31403,-0.21637,1.1253,0.41434,0.77759,0.20421,0.70657,0.53273,-0.67276,-0.65656,0.6997,-0.06428,-0.13546,-0.15055,0.99804,1.4673,-0.47155,-0.056436,0.84609,-0.23068,-0.55114,0.68975
CATMA5A25890,-0.23072,0.82252,0.32512,0.13284,0.14406,0.005071,0.40953,-0.11252,-0.6367,-0.048073,0.21325,-0.046316,-0.35078,1.1023,-0.019882,-0.55825,-0.34621,0.1114,0.030302,-0.08142,0.19157,0.5152,-0.034952,0.20984,1.0547,0.4816,0.31078,0.14731,0.31811,-0.27275,-0.47217,-0.043207,0.29109,0.41192,-1.069,0.23357,-0.17453,0.015661,-0.26869,0.14587,0.19336,0.5926,-0.1583,0.61242,0.18635,0.01207,-0.21772,0.13986,1.9305,0.3349,0.62954,-0.04455,1.121,-0.14155,-0.33772,-0.42633,0.41828,-0.29794,-0.7107,1.4786,-0.37442,-0.45371,0.16175,-0.057764,-0.11803,-0.037838,0.25868,0.88605,0.33225,-0.24331,0.93084,-0.33266,0.9762,0.24755,0.30857,0.14661,1.8351,0.40313,0.45084,-0.52105,-0.31271,-0.37122,-0.28615,-0.0023692,-0.43072,-0.24417,-0.5184,0.13874,-0.32606,-0.1705,2.1396,-0.77657,2.3056,0.32096,0.29337,-0.034746
CATMA5A31940,4.4307,4.8735,4.7911,5.8201,5.9587,5.576,5.9084,5.849,5.2832,5.5423,5.0275,4.5254,4.5054,3.0696,5.6512,4.3986,4.9856,4.9222,4.951,4.5506,4.2185,4.3184,5.4783,4.4515,3.9397,5.6269,5.0988,6.1254,5.7446,5.6146,5.452,5.2047,5.3527,5.93,4.8931,5.5529,3.9876,4.1072,4.0583,5.4324,5.4681,4.392,4.5189,5.0629,4.9347,5.2165,4.6681,4.7428,4.1539,6.3376,5.353,6.2896,5.5844,5.1654,5.4391,5.3933,5.261,5.6974,4.5142,3.9851,3.569,4.0946,4.6662,5.1085,5.0319,4.4598,4.8672,3.7326,5.3032,5.0448,4.7771,4.2209,4.1886,4.284,5.4681,5.8331,4.7683,5.6614,5.3313,5.2017,5.1002,5.0642,4.4867,4.8576,4.1454,4.0971,5.0368,4.845,4.753,5.5496,2.9838,5.1394,3.342,4.1246,5.0121,4.618
Code proper (BHC is from Bioconductor):
library(argparse)
library(RColorBrewer)
library(BHC)
library(parallel)
library(gplots)
#data prep and clustering, to get dendrograms etc as shown in plot
data = read.csv('input.csv',header=TRUE,row.names=1,check.names=FALSE)
genes = rownames(data)
samples = colnames(data)
data = data.matrix(data)
standardisedData = (data-mean(data))/sd(data)
samples = as.numeric(samples)
hc = bhc(standardisedData, genes, timePoints=samples, dataType='time-course', verbose=TRUE)
#the plotting proper
png('heatmap.png',width=6,height=6,units='in',res=300)
heatmap.2(standardisedData, Colv=NA, Rowv=hc, tracecol=NA, scale="none", col=brewer.pal(11,'RdBu'))
#heatmap.2(standardisedData, Colv=NA, Rowv=hc, tracecol=NA, scale="none", col=brewer.pal(11,'RdBu'), margins=c(3,10)) <- this fixes it on a single-case basis
dev.off()
I would suggest just giving it a fairly wide default margin, such that it should be clipped even with longer labels, e.g.:
heatmap.2(standardisedData, Colv=NA, Rowv=hc, tracecol=NA, scale="none", col=brewer.pal(11,'RdBu'), margins=c(14, 14))
The default margin size is (5,5). The above increases the both the column and row margins, but you can increase just one or the other as well.
If you want to be more precise, you could try using max(strwidth(rownames(standardisedData))) to determine the amount of space needed by the largest label, and then convert that into the units expected by par(mar=*) (what heatmap.2() uses to specify plot margins.)
I think this should do the trick:
# determine margins to use
png('/tmp/trash', width=6,height=6,units='in',res=300)
plot.new()
margin_width = max(strwidth(rownames(standardisedData), units='inches')) * par('fin')[1]
dev.off()
#the plotting proper
png('heatmap.png',width=6,height=6,units='in',res=300)
heatmap.2(standardisedData, Colv=NA, Rowv=hc, tracecol=NA, scale="none", col=brewer.pal(11,'RdBu'), margins=c(5, margin_width))
dev.off()

How do I exclude parameters from an RDA plot

I'm still relatively inexperienced manipulating plots in R, and am in need of assistance. I ran a redundancy analysis in R using the rda() function, but now I need to simplify the figure to exclude unnecessary information. The code I'm currently using is:
abio1516<-read.csv("1516 descriptors.csv")
attach(abio1516)
bio1516<-read.csv("1516habund.csv")
attach(bio1516)
rda1516<-rda(bio1516[,2:18],abio1516[,2:6])
anova(rda1516)
RsquareAdj(rda1516)
summary(rda1516)
varpart(bio1516[,2:18],~Distance_to_source,~Depth, ~Veg._cover, ~Surface_area,data=abio1516)
plot(rda1516,bty="n",xaxt="n",yaxt="n",main="1516; P=, R^2=",
ylab="Driven by , Var explained=",xlab="Driven by , Var explained=")
The produced plot looks like this:
Please help me modify my code to: exclude the sites (sit#), all axes, and the internal dashed lines.
I'd also like to either expand the size of the field, or move the vector labels to all fit in the plotting field.
updated as per responses, working code below this point
plot(rda,bty="n",xaxt="n",yaxt="n",type="n",main="xxx",ylab="xxx",xlab="xxx
Overall best:xxx")
abline(h=0,v=0,col="white",lwd=3)
points(rda,display="species",col="blue")
points(rda,display="cn",col="black")
text(rda,display="cn",col="black")
Start by plotting the rda with type = "n" which generates an empty plot to which you can add the things you want. The dotted lines are hard coded into the plot.cca function, so you need either make your own version, or use abline to hide them (then use box to cover up the holes in the axes).
require(vegan)
data(dune, dune.env)
rda1516 <- rda(dune~., data = dune.env)
plot(rda1516, type = "n")
abline(h = 0, v = 0, col = "white", lwd = 3)
box()
points(rda1516, display = "species")
points(rda1516, display = "cn", col = "blue")
text(rda1516, display = "cn", col = "blue")
If the text labels are not in the correct position, you can use the argument pos to move them (make a vector as long as the number of arrows you have with the integers 1 - 4 to move the label down, left, up, or right. (there might be better solutions to this)

Output Stem and Leaf Plot to Image

I'm trying to output a Stem and Leaf plot in R as an image. I'm not sure if there's a nice library which can accomplish this but below is some of the code I've tried.
jpeg(filename="stem.jpeg",width=480,height=480, units="px",pointsize=12)
plot.new()
tmp <- capture.output(stem(men, scale = 1, width = 40))
text( 0,1, paste(tmp, collapse='\n'), adj=c(0,1), family='mono' )
dev.off()
This above code resulted in the data being saved, but it looks very blurry and the plot gets cut off pretty badly. When adding a histogram to an image, R seems to do a good job to scale everything to fit in the size of the image.
jpeg(filename="stem.jpeg",width=480,height=480,
units="px",pointsize=12)
stem(men, scale = 1, width = 40)
dev.off()
This created the image but had no content within it.
Any ideas? Thanks!
That's because stem and leaf plots produce text not images. You can save the text as follows using the sink command: http://stat.ethz.ch/R-manual/R-devel/library/base/html/sink.html
sink(file=“Stem.txt”)
stem(men, scale = 1, width = 40)
sink(file=NULL)
unlink("stem.txt")
To export a stemplot as graphics, you can use a vector graphics format, such
as .eps, .pdf, or .emf. For example, a windows metafile:
win.metafile("stem.wmf", pointsize = 10)
plot.new()
tmp <- capture.output(stem(mtcars$mpg))
text(0,1,paste(tmp,collapse='\n'),family='mono',adj=c(0,1))
dev.off()

R image() / image.plot() giving different results while drawing or exporting big matrix

I have a big matrix (about 150 000 rows x 4 columns) ordered by one of the columns. I wanted to make a heat map using image() function but each time I change margin, or export resolution even by few pixels and the heat map gets redrawn it gives me drastically different results.
The code I use is:
image.plot(x=c(1:4),
y=seq(0,86945, by = 1),
z=LEfinalMatrixT,
col = mypalette,
axes = F,
ylab='',
xlab='',
xaxs = "i",
yaxs="i",
horizontal=F,
ylim=c(0,86945),
axis.args = list(cex.axis=1.2, at= seq(-3,1,by=1),labels = c("-3","-2","-1"," 0"," 1")),
legend.mar = 8,breaks = seq(-4,1.5,by=0.5))
Here are two images exported by running above code. One in 1200x1200px and second in 1199x1201px.
I'm new here and can't post images directly to the post but here are the links:
http://i62.tinypic.com/2uhv813.png
http://i59.tinypic.com/2irtfd5.png
If you look closer differences are huge and may highly impact the findings. Did any of you guys had similar problem? Is there a way to fix it?

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