Hi all,
I have a gene expression data matrix consists of about 10000 rows that represent genes and 20 columns represent 20 samples belonging to 2 different groups (10 samples per group).
I want to prove that the variance between the 10 samples of the first group is more than the variance between the 10 samples of the second group.
Analysis of Variance (ANOVA) methods may not work here (not sure of that) because it gives bad p-value as the number of variables (genes) are much much more than the number of observations (samples). Do I need to remove correlated genes, or cluster genes? is there any better solution for that?
Thanks in advance.
I have a gene expression data matrix consists of about 10000 rows that represent genes and 20 columns represent 20 samples belonging to 2 different groups (10 samples per group).
I want to prove that the variance between the 10 samples of the first group is more than the variance between the 10 samples of the second group.
Analysis of Variance (ANOVA) methods may not work here (not sure of that) because it gives bad p-value as the number of variables (genes) are much much more than the number of observations (samples). Do I need to remove correlated genes, or cluster genes? is there any better solution for that?
Thanks in advance.
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