Gregory B Gloor

Abstract In high-throughput sequencing (HTS) studies, sample-to-sample variation in sequencing depth is driven by technical factors, and not by variation in the scale (e.g., total size, microbial load, or total mRNA expression) of the underlying biological systems.

Abstract The application of '-omics' technologies to study bacterial vaginosis (BV) has uncovered vast differences in composition and scale between the vaginal microbiomes of healthy and BV patients.

Abstract Though statistical normalizations are often used in differential abundance or differential expression analysis to address sample-to-sample variation in sequencing depth, we offer a better alternative. These normalizations often make strong, implicit assumptions about the scale of biological systems (e.g., microbial load). Thus, analyses are susceptible to even slight errors in these assumptions, leading to elevated rates of false positives and false negatives.