Evaluating Combined Latent Variable Corrections in Differential Expression Analysis

This study investigates the effectiveness of combining transcriptomic surrogate variables and genotype principal components to correct latent variables in differential expression analysis. The research aims to determine whether simultaneous correction improves biological validity and reproducibility compared to using either method alone. This approach addresses confounding from technical, biological heterogeneity, and population stratification in transcriptomic datasets.

Originally published by gnews