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jean — Molecular Biology & Genomics

quantify_dpcr

Read-only

Digital PCR (dPCR) partition counts to absolute concentration, with no standard curve. Positives and accepted partitions become lambda = -ln(1 - k/n), lambda becomes copies per uL through the partition volume and the dilution chain, and the confidence interval is carried on the lambda scale under any of eleven published binomial interval methods. Returns the dMIQE-2020 occupancy QC beside every reading, so a well with no positives, or one saturated past 95% occupancy, is reported as such rather than as a number.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
wellsYesthe well table: `Well,Sample,Target,Positives,Partitions`. Instrument column names are accepted as they are printed (Bio-Rad's `AcceptedDroplets`, QIAcuity's `Valid partitions`), so a real export needs no renaming.
_filesNoThe project: record references shaped like _subject. Their records become library documents a tool names in sequences/parts/document; a trace or alignment is found by file name.
_subjectNoThe record to act on: exactly one of sequence, accession (+source), sample (an id from list_samples) or file ({name, text} or {name, base64}); record_index picks one record of several.
ci_methodNowhich binomial confidence interval is carried onto the lambda scale. Values: agresti-coull (Agresti–Coull), asymptotic (Asymptotic (normal approximation)), bayes (Bayes (Jeffreys prior, highest-density)), cloglog (Complementary log-log), exact (Exact (Clopper–Pearson)), logit (Logit), lrt (Likelihood ratio), probit (Probit), prop.test (Score test inverted, continuity-corrected), profile (Profile likelihood), wilson (Wilson score). Advanced.wilson
volume_cvNocoefficient of variation of the partition volume, as a percentage. Ignored under the `poisson` model. There is no universal value and inventing one would fabricate the exact quantity the correction consumes - the one figure this repo has a published source for is QuantStudio 3D chip (Majumdar 2017) at 3.03 %, and that paper says the vendor re-estimates it per chip rather than treating it as a platform constant. In %. Only applies when volume_model is normal or truncated.
conf_levelNoconfidence level for the interval. Advanced.
ratio_targetNothe assay whose COPY NUMBER you want, named as it appears in the table's Target column. Leave it and `ratio_reference` unset and no copy number is reported at all — a guessed pair is a fabricated comparison.
volume_modelNohow partition-volume SPREAD is handled (QP-5c). `poisson` is the standard estimator and assumes every partition holds the same volume. The two Poisson-Plus arms (Majumdar 2017) integrate the Poisson negative probability over a normal volume distribution and invert it: `normal` is the closed-form Eq (9), `truncated` the exact Eq (13) over a normal cut off at zero, which is the honest density because a partition cannot hold a negative volume. The spread biases the standard estimate DOWNWARD, hard at high occupancy and not at all at low. Values: poisson (Standard Poisson (no correction)), normal (Poisson-Plus, normal (Eq 9)), truncated (Poisson-Plus, truncated normal (Eq 13)).poisson
dilution_factorNofold dilution applied to the sample before the reaction (2 = diluted 1:2). Advanced.
ratio_referenceNothe assay it is measured against: the single-copy or known-ploidy reference, again by its Target name.
merge_replicatesNopool wells that share a sample and target before quantifying. Replicates of one measurement are one measurement, and pooling the COUNTS is the correct way to combine them, never averaging concentrations.
reference_copiesNocopies of the REFERENCE target per genome. 2 is a diploid autosome, 1 a haploid or single-copy locus. Advanced.
reaction_volume_ulNototal reaction volume, for copies per reaction. In uL.
template_volume_ulNovolume of template added to the reaction. Left at 0 the sample-concentration row is omitted rather than guessed. In uL. Advanced.
partition_volume_nlNomean volume of ONE partition. A per-platform constant, not a universal one (Bio-Rad QX200 approx 0.85 nL, QIAcuity 26k approx 0.34 nL, QuantStudio 3D approx 0.755 nL), and dMIQE 2020 requires it to be reported with the result. In nL.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
rowsYesone reading per well, or per pooled replicate group: occupancy, lambda with its interval, and every concentration the supplied volumes support
countYeshow many readings were produced
ratiosYestarget-vs-reference copy number per sample, with the exact Poisson rate ratio and its interval rescaled onto the concentration scale the number is on. Empty when no assay pair was named — never a guessed pair
flaggedYesreadings carrying at least one dMIQE occupancy flag
ciMethodYesthe interval method that produced the bounds: a CI without its method is not comparable
volumeModelYeshow partition-volume spread was handled. `poisson` means it was not — a concentration without this is not comparable with one that was corrected
volumeCvPercentYesthe volume spread the correction used, echoed for the same reason as the partition volume: it changed the number
partitionVolumeNlYesthe partition volume the concentrations were computed at, echoed because dMIQE requires it to travel with the number

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/non-destructive, so the bar is lower, but the description adds real behavioral content: dMIQE-2020 occupancy QC is returned beside every reading and degenerate wells (no positives, >95% saturation) are reported as such rather than as a number. It also notes that leaving ratio_target/ratio_reference unset suppresses copy number rather than guessing.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences, front-loaded with purpose and derivation, then edge-case reporting. Dense but nearly every clause adds information; a couple of clauses are long but none are filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 15-parameter tool with an output schema, the description covers the computation, the eleven CI methods, edge-case reporting, and the required QC standard. Since the output schema exists, return values need not be detailed, and what remains absent (platform-specific partition volumes) is already covered in the parameter schema text.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% so the baseline is 3, but the description adds conceptual linkage: positives/partitions, partition volume, and dilution chain all feed one lambda, and the CI is carried on the lambda scale under the chosen binomial method. That ties several parameters into a single model rather than merely restating them.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource (dPCR partition counts to absolute concentration) and pins down the mechanism: lambda = -ln(1 - k/n), partition volume, dilution chain. It is clearly distinguishable from the standard-curve qPCR siblings (call_cq, bootstrap_cq, simulate_taqman_curve) via 'with no standard curve'.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The 'no standard curve' framing implies this is the absolute-quantification path rather than the standard-curve qPCR path, but no sibling is named and no when-not condition is stated. It also lacks prerequisites (what a valid well table must contain) beyond what the wells schema implies.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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