A Critique of Differential Abundance Analysis, and Advocacy for an Alternative

TL;DR

This paper critiques the reliance on differential abundance analysis in genomic data, highlighting its limitations, and proposes an alternative ratio-based biomarker framework that is more flexible and reliable for various analyses.

Contribution

It introduces a novel ratio-based biomarker analysis framework as a superior alternative to differential abundance analysis in genomic studies.

Findings

Identifies limitations of differential abundance analysis

Proposes ratio-based biomarker analysis as an effective alternative

Demonstrates flexibility of the new framework for various applications

Abstract

It is largely taken for granted that differential abundance analysis is, by default, the best first step when analyzing genomic data. We argue that this is not necessarily the case. In this article, we identify key limitations that are intrinsic to differential abundance analysis: it is (a) dependent on unverifiable assumptions, (b) an unreliable construct, and (c) overly reductionist. We formulate an alternative framework called ratio-based biomarker analysis which does not suffer from the identified limitations. Moreover, ratio-based biomarkers are highly flexible. Beyond replacing DAA, they can also be used for many other bespoke analyses, including dimension reduction and multi-omics data integration.