Pooled QC Cv Gate

Gate pooled metabolomics QC by coefficient of variation.

Description

Pooled-QC variation summarizes measurement repeatability relative to the mean.

Pooled-QC variation summarizes measurement repeatability relative to the mean. This calculation uses population standard deviation, dividing squared deviations by n.^[1]

Gate pooled metabolomics QC by coefficient of variation.

When to use Pooled QC Cv Gate

Use this tool to gate pooled metabolomics QC by coefficient of variation.

Prepare the measured profile, formula counts, upstream model outputs or caller-defined reference criteria requested. Keep paired entries aligned and units, sample basis and preprocessing consistent.

How to use Pooled QC Cv Gate and understand its results

Prepare the measured profile, formula counts, upstream model outputs or caller-defined reference criteria requested. Keep paired entries aligned and units, sample basis and preprocessing consistent.
Enter pooledQcMeasurements, maximumCvPercent using the field table and calculation rules, then run the tool.
Read cvPercent, passes. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
pooledQcMeasurements	Pooled qc measurements	list of number	Required
maximumCvPercent	Maximum cv percent	number	Required

Enter at least two nonnegative measurements with positive mean and a finite CV maximum. Return CV and inclusive CV≤maximum gate.

CV%=100 sqrt(Σ(x−mean)²/n)/mean

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
cvPercent	Cv percent	number
passes	Passes	boolean

json

{
  "input": {
    "pooledQcMeasurements": [
      9,
      10,
      11
    ],
    "maximumCvPercent": 10
  },
  "output": {
    "cvPercent": 8.16496580927726,
    "passes": true
  }
}

Limitations and assumptions

The maximum is caller-selected and may be negative. No batch stratification, drift removal or analytical acceptance standard is inferred.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Lists are limited to 100,000 entries; the rules above may require smaller limits. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors. A successfully returned false flag is an evaluated outcome; its meaning is explained above.

Alternative or Complementary methods

Use Signal Drift Correction: Correct injection-order signal drift using aligned QC trend estimates. For a complementary task, use Unit Variance Scaling: Autoscale a feature to zero mean and unit population variance.

References

Pooled QC Cv Gate — tool.io

Similar or alternative tools

Signal Drift Correction
Correct injection-order signal drift using aligned QC trend estimates.
Unit Variance Scaling
Autoscale a feature to zero mean and unit population variance.