ClaridaClarida

The qPCR platform from the team behind MIQE, geNorm & qbase+

New research question?One workflow, from design to report.

Clarida adapts to your science, not the other way around.

  • Reproducible by design
  • Built on peer-reviewed methods
  • Your data, always exportable
Start your first experimentBook a demo

MIQE Guidelines

Co-authored by our team

qbase+ & geNorm

Proven analysis methods, built in

No lock-in

Export everything, anytime

Full traceability

Every result traces to its raw data

The question changes. The grind doesn't.
It should.

New gene targets, new plate layout, new export, new analysis - the same 2+ hours of reformatting you did last month. Across 5 disconnected tools that don't talk to each other, where 1 in 3 errors traces back to a misplaced paste.

5 disconnected tools per experiment

2+ hrs lost reformatting per dataset

1 in 3 errors from copy-paste

What if one workflow could handle every experiment?

Five stages. Zero gaps.

So you can focus on the science.

Clarida - DefineAuto-saved
Research Question
Is BRCA1 expression reduced in triple-negative breast cancer tissue compared to matched healthy controls?
Consider narrowing to stage II-III per Chen et al.Apply
References
Chen et al. (2023) — BRCA1 in TNBCPubMed
TCGA BRCA1 expression — TNBC cohortPublic DB
Lab SOP — TRIzol RNA extraction v2.1Protocols.io
Ready for Design phase
Two-group comparison layout
Candidate reference genes identified
NTC controls on every plate
Done
Question
Background
Hypothesis
Type
Refs
Protocol
6/6
Define

Your analysis is only as good as your question

Clarida starts before the plate - with your research question, hypothesis, and supporting literature. Your whole team sees the same context, and every decision is logged.

No more reconstructing "why did we choose those reference genes?" from six-month-old email threads.

Clarida - DesignAuto-saved
TNBC (n=25)Controls (n=16)NTC (×3)BRCA1 GOIGAPDH REFACTB REF
Assay-blocked layout · 378 / 384 wells · 98% utilization
BRCA1 GAPDH ACTB
PowerUp SYBR
10 µL rxn
CFX384
Bio-Rad
3-step
40 cycles
Done
Samples
Assays
Mix
Instrument
Layout
Protocol
6/6
Design

The plate should match the experiment, not the other way around

Your plate layout carries every upstream decision - sample groups, reference genes, controls, replicates. Clarida makes that structure visible, reusable, and impossible to lose when you move to execution.

Switch from a 96-well validation to a 384-well screen without rebuilding your sample list from scratch.

Clarida - ExecuteAuto-saved
Collect
Mix
Fill
Run
Step 1 of 3 — Distribute BRCA1 assay mix
10 µL/well·Tube A1·Cols 1–8, Row I
Plate Fill55%
208 / 378 wellsRow I active
G
I
active
J
BRCA1 GAPDH ACTB
NTC wells (P4-P6) — mix only, no template. Verify before sealing.
Done
Materials
Mix
Plate fill
NTC
Instrument
Run
4/6
Execute

Your design is airtight - until the pipetting starts

Your plate layout, volumes, and sample positions are already defined upstream. Clarida turns that structure into step-by-step bench guidance - tracking fill progress well by well, flagging NTC positions before you seal, and logging every action so nothing is reconstructed from memory.

Switch to hands-free mode and navigate the protocol while gloved - no laptop touch required.

Clarida - AnalyzeAuto-saved
QC
Ref genes
Normalize
Statistics
Review
Ref genes: GAPDH + ACTB selectedgeNorm V<0.15
BRCA1 ExpressionFC 0.37 · p<0.001
0.00.51.01.5Controln=16TNBCn=25FC 0.372.7× downp < 0.001
Mann-Whitney U·Mean CNRQ: 0.37 vs 1.00·95% CI [0.31–0.43]
Matches Chen et al. (2023) — 2-3× in stage II-III TNBC
Done
QC
Ref genes
Normalize
Statistics
PI review
4/5
Analyze

Your data is only as honest as your normalization

Your raw Cq values are in. Clarida validates reference gene stability, flags outliers, normalizes with efficiency correction, and runs your statistics - before you’ve opened Excel. MIQE-compliant at every step, built by the scientists who wrote the guidelines.

No more wondering whether GAPDH was actually stable across your treatment groups - geNorm runs automatically on import.

Clarida - ReportAuto-saved
Figures
Methods
MIQE
Review
Export
Proposed Conclusions2 accepted · 1 pending

BRCA1 shows 2.7× downregulation in TNBC (FC 0.37, p<0.001).

Accepted

GAPDH + ACTB most stable (geNorm M=0.34), two refs sufficient.

Accepted

4/378 wells flagged (1.1%) — exclusion does not alter significance.

AcceptEdit
MIQE Compliance47/51Essential14/17Desirable
C3: RNA integrity (RIN) — not provided
H5: LOD — not determined for BRCA1
Export
PDF Report
PowerPointExcelRDML
Done
Figures
Methods
MIQE
PI approval
Export
4/5
Report

Your results are reproducible - until someone asks how

Your results are clear, but the paper isn’t. Clarida auto-generates publication-ready figures, writes your methods from the experiment record, checks MIQE compliance across 51 essential items, and proposes conclusions you review and accept - so you submit the paper, not just the data.

Reviewer asks "what was your primer efficiency?" - the answer is one click away.

1 / 5

One workflow. Whatever the question.

Same five steps, different research questions - from hypothesis to actionable report.

Gene expression

“Is my candidate gene upregulated in treated vs. control samples?”

3+ tools, 45 min per dataset
Cq to figures in minutes

MIQE-compliant fold changes - normalized, plotted, reviewer-ready.

Replace your Excel + GraphPad pipeline

Reference gene validation

“Which reference genes are most stable across my tissue panel?”

3+ tools for separate geNorm analysis
geNorm ranking, built in

The gold-standard algorithm, built by its original author.

Same science as qbase+, modern workflow

Quality control

“Is there batch-to-batch variation in my cDNA synthesis?”

Weeks lost from one bad batch
Pass/fail per batch, catch it early

CV analysis, outlier flagging, audit-ready QC reports.

The QC your spreadsheet can’t do

Copy number variation

“Did my gene edit integrate, and how many copies?”

Error-prone ratio calculations in Excel
Copy number calls with confidence intervals

Purpose-built CNV workflow - not expression analysis repurposed for ratios.

Confidence intervals, not guesswork

What researchers are saying

From peer-reviewed journals to lab bench conversations - the problem is real.

“The majority of published RT-qPCR data are likely to represent technical noise.”

Bustin & Nolan

European Journal of Clinical Investigation, 2017

“Compliance remains patchy, and in many cases, entirely superficial.”

Bustin

Int. J. Mol. Sci., 2025

“Data analysis includes many time-consuming and cumbersome steps, which can lead to mistakes and misinterpretation of data.”

Maussion et al.

Scientific Reports, 2021

“Compliance with 15 essential MIQE criteria was low — median of 40%. Normalisation process: 3%.”

Abdel Nour et al.

PLOS ONE, 2014

17,000+citations

The MIQE Guidelines

Bustin, Hellemans, Vandesompele et al.

Clinical Chemistry, 2009

Co-authored by our team

“17 years since original MIQE guidelines and such a low impact. Sad it is.”

Richard Nadvornik

Executive Director, SEQme

“13% to 1% reporting efficiency, that's bonkers!! Quality has progressively slipped globally.”

James Hassall

CEO, SHARD DIAGNOSTICS

“Nearly every research user is churning out unreproducible junk. No one follows the MIQE guidelines.”

30-year qPCR industry veteran

r/bioinformatics

“MIQE is not followed because, at best, it is an afterthought. What if it were ever present in a researcher’s workflow?”

Researcher

r/bioinformatics

“The tech rep mentioned his custom Excel sheets. That suggests everyone is making glued-together spreadsheets.”

Researcher

r/bioinformatics

“Fascinating this is still the issue… I found it to be true 20 years ago in grad school.”

Researcher

r/bioinformatics

23,000+citations

The geNorm Algorithm

Vandesompele et al.

Genome Biology, 2002

Created by our team

“Vendors have basically given up and stripped out features from their software because no one used them.”

30-year qPCR industry veteran

r/bioinformatics

“I end up having to export and manually convert a lot of things. Definitely a lot of unsanitary data modifying.”

Researcher

r/bioinformatics

“Excel is the go-to because of its flexibility. Unfortunately, this also allows sub-par record keeping.”

Researcher

r/bioinformatics

3,800+citations

The qBase Framework

Hellemans, Vandesompele et al.

Genome Biology, 2007

Created by our team

“Scientists spend hours reformatting, relabeling, and chasing metadata just to get to the stats.”

r/bioinformatics discussion

45 upvotes

“It would be great if there were tools that retain the freedom of Excel while assisting in the error-prone steps.”

Researcher

r/bioinformatics

Free tools for common qPCR challenges

No account. No setup. Just answers.

Clarida - Reference gene finder
Gene Stability Ranking (geNorm M-values)Average Expression Stability (M)0.00.10.20.30.40.50.60.70.8Genes (ordered by stability)hBActhTUBA1AhGAPDHhSDHAhTBCAh18shU6hRNU48hRNU44hRNU47

Reference gene finder

Paste your Cq values, get a stability ranking. The same geNorm algorithm used in 20,000+ publications - no install, no login.

Try it free

Spend time on science, not the pipeline.

Free to start. No credit card required. Export your data anytime.

Start your first experimentTalk to a qPCR expert