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Hello everybody
I have a long list of genes and different samples, and my goal was to look at how some of these genes behave in different life stages of my ant. Fairly simple, I annotated the interesting genes.
However, I have not found a good technic to plot only these genes.
Here is the commands I use for a "normal" heat map, when I want for example to look at 100 most DE genes.
library(gplots)
scale <- Dnorm$samples$lib.size*Dnorm$samples$norm.factors
normCounts <- round(t(t(counts)/scale)*mean(scale))
heatmap(log(normCounts[Dc[1:100],]+1))
But with these technic I go through EdgeR first and then run the heatmap directly.
So I am not really sure what would be the best way to do that if I only use some genes, obviously if I run EdgeR with only 10 genes, the normalization and the rest of EdgeR commands are skewed and don't fit anymore.
Does anyone have experience with that or knows what would be the best thing to do for me?
Thanks for your help
Claire
I have a long list of genes and different samples, and my goal was to look at how some of these genes behave in different life stages of my ant. Fairly simple, I annotated the interesting genes.
However, I have not found a good technic to plot only these genes.
Here is the commands I use for a "normal" heat map, when I want for example to look at 100 most DE genes.
library(gplots)
scale <- Dnorm$samples$lib.size*Dnorm$samples$norm.factors
normCounts <- round(t(t(counts)/scale)*mean(scale))
heatmap(log(normCounts[Dc[1:100],]+1))
But with these technic I go through EdgeR first and then run the heatmap directly.
So I am not really sure what would be the best way to do that if I only use some genes, obviously if I run EdgeR with only 10 genes, the normalization and the rest of EdgeR commands are skewed and don't fit anymore.
Does anyone have experience with that or knows what would be the best thing to do for me?
Thanks for your help
Claire
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