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This study delves into gene expression patterns by utilizing log-transformed p-values and log2 fold changes to assess proportions. Through comprehensive statistical analyses, we aim to identify significant variations in gene expression levels under different conditions. By transforming p-values using the logarithm base 10, we enhance interpretability and facilitate the comparison of expression ratios using log2 fold changes. This approach will contribute to a better understanding of the molecular mechanisms driving biological processes and disease states.
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