What statistical method was used to assess the correlation between bacterial counts and NF-κB or CD11b+ expression?

• A. Pearson correlation coefficients
• B. Spearman correlation coefficients
• C. Linear regression
• D. Chi-square test

Answer: (B)

The key idea is using a nonparametric measure of association when the data may not be normally distributed or the relationship isn’t strictly linear. Spearman correlation looks at how well the ranked values of bacterial counts align with the ranked expression levels of NF-κB or CD11b+, capturing monotonic relationships without assuming linearity. This makes it robust to skewed counts, outliers, and the typical non-normal distribution of expression data, providing a reliable sense of whether higher bacterial load tends to accompany higher (or lower) expression. Pearson correlation would require a linear relationship and normal distributions, which aren’t guaranteed here. Linear regression focuses on predicting one variable from another with specific assumptions about residuals, not just measuring association. Chi-square is for categorical data, which isn’t appropriate for continuous or ordinal expression measurements.