Why is the answer not just positives divided by partitions?

Because a positive partition may have held more than one molecule. The concentration is recovered from the negative fraction instead, which is what makes digital PCR absolute rather than relative.

What happens when every partition is positive?

The negative fraction is zero, so the estimate is undefined. The tool says the sample is above the assay range and needs diluting, rather than printing a number that would be wrong.

Do I have to use droplets?

No. Any partitioned platform works — the partition volume is a field, because it differs between droplet, chip and nanoplate instruments and dMIQE asks for it to be reported.

Amplify

Digital PCR

Turn partition counts into an absolute concentration. Paste the well table an instrument exports (positives and accepted partitions) and read copies per microlitre with a confidence interval, without a standard curve and without uploading the file anywhere. Two assays in the same sample give a copy number by the exact Poisson ratio, which is how a duplex copy-number experiment is read.

Open the editor Open the qPCR & digital PCR sample

The real qPCR corpus: ΔΔCt (separate + same-tube), a standard curve, a significance table, Vandesompele 2002 geNorm in wide and long form, real amplification curves. Opens on the human GAPDH and MYC transcripts those experiments actually measure, plus a 72 bp miRNA precursor that walks Design right up to its length limit

What it does

01Absolute quantification from partition counts by Poisson statistics, with no standard curve
02Confidence intervals by eight published binomial methods, transformed onto the copies-per-partition scale
03Concentration in copies per microlitre of reaction, per reaction, and back-calculated to the original sample through the dilution chain
04Replicate wells pooled as one larger experiment rather than averaged
05Copy-number and duplex ratio between two assays by the exact Poisson rate-ratio interval
06Occupancy and precision quality checks that name the problem, including saturation where the estimate is undefined
07A real 28-well droplet copy-number run bundled as a worked example

What it runs on

The Poisson transform and its confidence intervals are ported from the R packages the field uses (dpcR, binom, rateratio.test) and validated byte-for-byte against them; the precision formula is checked against a Monte-Carlo simulation rather than against itself. The panel runs on @ports/discover, @ports/eds, @ports/melt, @ports/qpcr, @ports/rdml, @ports/workflow.

Everything runs client-side. Files are parsed in the browser and projects are saved on this machine, so an unpublished sequence is never uploaded.

Questions

Why is the answer not just positives divided by partitions?: Because a positive partition may have held more than one molecule. The concentration is recovered from the negative fraction instead, which is what makes digital PCR absolute rather than relative.
What happens when every partition is positive?: The negative fraction is zero, so the estimate is undefined. The tool says the sample is above the assay range and needs diluting, rather than printing a number that would be wrong.
Do I have to use droplets?: No. Any partitioned platform works — the partition volume is a field, because it differs between droplet, chip and nanoplate instruments and dMIQE asks for it to be reported.

Also searched as

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