Analysis types

ORA vs Enrichment (two ways to run TaxSEA)

TaxSEA supports two complementary analysis modes: Enrichment and ORA (Over-Representation Analysis).
They answer related but distinct questions and are appropriate in different situations.

Enrichment (rank-based)

What it does (in plain terms)

You provide TaxSEA with a ranked list of taxa (for example from most increased to most decreased).
TaxSEA then asks:

Do the members of a given taxon set tend to appear unusually high or low in this ranking?

Importantly, all taxa are used, not just those passing a significance threshold.

When to use it (recommended in most cases)

Use Enrichment when:

You have differential abundance results (e.g. log fold changes, test statistics, signed p-values)
Taxa can be meaningfully ordered by strength and direction of effect
You want to avoid hard cutoffs such as “significant vs not significant”

Pros

Uses all taxa, not only a selected subset
Less sensitive to arbitrary thresholds
More stable when signal is spread across many taxa
Can detect subtle, coordinated shifts across a taxon set

Cons

Requires a sensible ranking metric
Not appropriate if the data are strictly presence/absence with no meaningful ordering

ORA (Over-Representation Analysis)

What it does (in plain terms)

You provide TaxSEA with a list of taxa of interest (your “hits”), along with a background universe.
TaxSEA then asks:

Are taxa from this set appearing in my hit list more often than expected by chance?

This is a classic enrichment-of-hits approach using contingency tables.

When to use it

Use ORA when:

Your data are naturally binary (presence vs absence, detected vs not detected)
A ranked statistic is not meaningful or not available
You have a strong, biologically justified threshold defining your taxa of interest

Pros

Simple and intuitive interpretation
Works well for presence/absence style data
Appropriate when only a hit list is available

Cons

Highly sensitive to how “hits” are defined
Discards information about effect size and ordering
Results can change substantially with small changes to thresholds

Recommended practice

In most microbiome differential abundance analyses, Enrichment is recommended whenever a reasonable ranking can be constructed (e.g. log fold change, Wald statistic, signed −log10 p-value). It makes fuller use of the data and avoids arbitrary cutoffs.

ORA should be used when ranking is not possible or not meaningful, particularly in presence/absence scenarios or when the scientific question explicitly concerns membership in a predefined hit list rather than graded shifts.

Both methods are valid; the choice depends on the structure of the data and the biological question being asked.