Image link https://ibb.co/zhHbMyL
I am using heatmap3 to create heatmap. I have 77 rows and 10 columns in reality but getting heatmap with only 38 rows with 10 columns. my code is as below
x <- Heatmap_data
x
y <- as.matrix(Heatmap_data)
y
class(x)
class(y)
library(heatmap3)
nrow(y)
ncol(y)
heatmap3(y, Rowv = NULL, Colv = NULL,
distfun = function(y) as.dist(1 - cor(t(y), use = "pa")), balanceColor = F, showColDendro = T, showRowDendro = F,
col = colorRampPalette(c("white", "firebrick3"))(1024),
method = "complete", ColAxisColors = 0,
RowAxisColors = 0, hclustfun = hclust, reorderfun = function(d, w)
reorder(d, w), symm = FALSE, scale = c("none"),
ColSideWidth = 0.4, file = "heatmap3.pdf", topN = NA, filterFun = sd,
returnDistMatrix = FALSE, margins = c(5, 5), cexRow = 0.2 + 1/log10(nrow(y)), cexCol = 0.2 +
1/log10(ncol(y)), lasRow = 2, lasCol = 2, labRow = NULL,
labCol = NULL, main = NULL, xlab = NULL, ylab = NULL,
keep.dendro = FALSE, verbose = getOption("verbose"), useRaster = if
(ncol(y) * nrow(y) >= 50000) TRUE else FALSE)
my data (truncated) looks like below (10 columns & 77 rows). Values are protein identities.
ORFs Aspergillus_nidulans Batrachochytrium_dendrobatidis Bifiguratus_adelaidae Botrytis_cinerea
STRG.198.1 55 0 0 39.394
STRG.428.1 86.301 88.889 87.302 90.411
STRG.1138.5 69.231 56.338 0 64.368
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UDAY.AGRI123 •
Hey Uday, there is no error here, per se. This was a relatively recent introduction in R whereby certain plotting functions now intelligently only show as many labels as can be reasonably read by the viewer.
We can replicate this 'issue' by simply modifying the size of the row [gene] names:
require(heatmap3)
mat <- matrix(rexp(2000, rate = 0.1), ncol = 20)
rownames(mat) <- paste0('gene', 1:nrow(mat))
colnames(mat) <- paste0('sample', 1:ncol(mat))
dev.new(width = 10, height = 8)
heatmap3(mat, cexRow = 3)
dev.new(width = 10, height = 8)
heatmap3(mat, cexRow = 1)
Kevin
Hi Kevin,
It is so simple, ate my time like anything, hehehe!!! Thanks, and much appreciated for your time in replying.
Uday
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written
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UDAY.AGRI123 •
This seems to partially work in my case since, after reducing cexRow enough, there is a point where no more gene names are added even if there are still gene names missing. Instead, the space between already plotted genenames is increased. Any way to fix this?
Then you can 'step through' the genes and set some to have values of "" (empty string), just for the purpose of visualisation.
You can also fit more genes via connectors with ComplexHeatmap: https://github.com/kevinblighe/E-MTAB-6141
At some point, however, it's just not feasible to try to show all genes in a heatmap.
"At some point, however, it's just not feasible to try to show all genes in a heatmap." That is actually my case, gene names would just not be readable if all were to be added, so I suppose in my case gene names showing would be more for aesthetic purposes? Perhaps it is possible to add genenames with highest variation in expression accross experimental conditions?
Hello. Why the highest variation?; what is the purpose of generating the heatmap? - is it just to have a heatmap for no other reason than just having the heatmap?
Hello. By highest variation i mean highest difference in expression between given experimental conditions. So from the list of differentially expressed genes used to make the heatmap i was thinking of having displayed genes with the biggest fold change since not all of them can be displayed.
I see what you mean. There is no problem in doing that, provided that you clearly state the fold change cut-off in the figure legend.
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are you trying to log transform values of 0?
I am not doing that, you can see how my data looks like in updated post. All numeric data is protein identity values and first column is gene names.
Do you see any errors or warnings?
I am not seeing any errors or warnings, simply the nice and beautiful output figure is popping up.
Please provide minimal dataset for reproducibility.
What do you mean by that ? are you saying to give my data to see how it looks or anything else you meant?
No, you don't have to share your data. I mean that
Many programs that do this kind of analysis have an option to remove "flat" data points, which are rows where there is not much difference between samples. I don't use
R, but my guess is thatfilterFun = sdcould be doing that. Even if that's not the case, looking into what rows are removed and what they have in common could help you figure this out.