Before choosing a probe-based approach, consider how the assay may shape interpretation.

Measure Biology, Not Probe Design

Don't Let Probe Design Define Your Biology

Probe based assays can make gene expression measurements depend on probe number, binding efficiency, and target region selection. Evercode WT uses reverse transcription-based whole transcriptome profiling to keep your data closer to the biology you set out to measure.

Probes Miss. Biology Doesn't.

Are You Measuring Gene Expression or Probe Design?

When probes miss a transcript, biology can look absent—leaving you unsure if it’s truly gone or just undetected.

If a probe does not bind well to a transcript, the biology may appear absent, even when it is present. That creates a false negative risk. In a discovery study, that missed signal could be a key pathway, biomarker, cell type-specific event, or therapeutic target.

If the signal is missing, how do you know whether it is biology or probe design?

PTPRK

Cell Types

Flex V2

GEM-X 3'

Evercode V4

PTPRK: A Real Signal That Looks Absent

PTPRK is an important gene expected to be expressed in both B cells and CD4 T cells, and that is what RT-based methods show, with consistent patterns across both GEM-X 3′ and Evercode V4. Flex V2, using a probe-based approach, misses PTPRK expression entirely in the B cell population. The signal is not gone, but it is undetected. Across many genes, RT-based methods agree while probe-based detection shows little, none, or different patterns, leaving you unsure whether a missing signal reflects biology or probe design.

What Could Appear Inflated?

Signal Level Does Not Always Mean Expression Level

Probe-based assays can assign multiple probes to the same gene, but those probes do not always produce similar counts.

When counts vary across probes, summed expression values can reflect probe design and performance rather than transcript abundance alone. That can make it harder to compare expression across genes, cell types, or datasets.

Probe-Dependent Signal: When Counts Reflect Probe Performance, Not Biology

When a gene is targeted by multiple probes, each binds a different region of the same transcript, and if they measured the same RNA abundance you would expect similar counts. Often they do not agree. For 7,470 genes the highest-counting probe produced more than twice the counts of the lowest for that same gene, for 1,378 genes the difference exceeded 10-fold, and for 161 it exceeded 100-fold. Because expression is summed across these probes, the final value reflects probe design and performance, not transcript abundance alone. More signal does not always mean more expression.

What Could Appear Meaningful?

A False Signal Can Look Biological

With probe based measurement, a signal can look like a biological discovery when it is actually a probe-driven artifact.

False positives can make it harder to separate true biology from assay-driven signal.

When a signal appears in one technology but is not supported by reverse transcription-based (RT) whole transcriptome methods, it can raise questions about whether the signal reflects the sample or the assay. In some cases, that signal could influence conclusions about cell state, disease relevance, or therapeutic potential.