Appreciate your suggestions. I will take a look some permutation approaches and other tools that could analyze the zero-inflated data.
Correlation analysis for low expressed genes
Dear all, I am doing a correlation analysis on few targeted genes and I found there some genes that are low expressed. For example, a gene expression data for two gene with 100 subjects below:
Gene A Gene B
Subject1 0 45
Subject2 0 42
Subject3 0 55
Subject4 0.1 78
Subject5 0.03 66
...
Subject98 0.09 69
Subject99 0 47
Subject100 0 44
However, there are many zero values in Gene A, and only three subjects are detected little gene expression on Gene A. Here is my question. Is it reasonable to use Spearman correlation to capture the relationship between Gene A and Gene B? I would greatly appreciate it if you kindly give me some feedback.
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One option is to use the samples with only non-zero expression values. Other option is to perform permutations and calculate a p-value.
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