Dear all, I'm trying to combine the normalized counts from 3 biological replicates into single columns of the normalized count matrix. I need it in order to "absolutely" analyze the expression of specific genes, for example - presenting expressions on heat maps (or other plots) and doing co expression analysis. I would like to emphasize that all 3 biological replicates are, in my point of view, identical, meaning, all are before any treatment, or all of them are after a specific treatment. Yet, I cannot treat them as technical replicates as they were taken from different biological samples. I know that Deseq2 can collapse technical replicates into a single column, but it is not intended for biological replicates (and I must say that I'm not fully understand why, if all "averaged" replicates represent the same treatment but I'm still a newbie and I accept the verdict). What alternatives do I have? Is it allowed to do a simple average on the normalized counts of each of the 3 samples converting it into a single normalized count?? Any suggestion would be highly appreciated.
Thank you so much!! I'll try that. If I understand correctly then a simple average of the 3 (for example) normalized count columns is what I need to do? For some reason, I had in my mind that a more careful averaging was required, something that takes into consideration some additional statistical properties, but I have no idea why I was thinking this way...
"is what i need to do"?
Yes to calculate the average scaled count, the above is the code you would use.
Hi if I have 12 samples with 3 biological replicates ( 36 sample total), and I want to create a matrix with row names as gene and columns as the average ( average of 3 replicate) normalized counts of 12 sample, how may I create that in R? TIA.
Hi if I have 12 samples with 3 biological replicates ( 36 sample total), and I want to create a matrix with row names as gene and columns as the average ( average of 3 replicate) normalized counts of 12 sample, how may I create that in R? TIA.
You can do this with the above code, plus a loop over the samples. I'd recommend getting some help from someone familiar with basic R scripting.
Thank you.
Curious if taking an average (mean) of (3) biological replicates if a best way to represent each sample data? is there any other statistical analysis that needs to be taken into account before taking average (mean), median or other?
This is just for descriptive summary, so mean of scaled counts is fine.
For statistical testing, we model the counts and their dispersion.
For plotting on a heatmap or otherwise, we recommend variance stabilization with
vst().Hi please let me know how to implement this code, specially [ dds$condition == "A"] this part. how it should be changed ?
What is =="A" here?