Population PC Outliers

Flag population-PC1 outliers relative to an explicitly supplied reference mean and standard deviation.

Description

A principal-component coordinate can be screened against an explicit reference distribution.

A principal-component coordinate can be screened against an explicit reference distribution. Standardizing by its reference mean and deviation gives a signed z score.

Flag population-PC1 outliers relative to an explicitly supplied reference mean and standard deviation.

When to use Population PC Outliers

Use this for the following task: Flag population-PC1 outliers relative to an explicitly supplied reference mean and standard deviation.

Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.

How to use Population PC Outliers and understand its results

Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
Enter sampleIds, pc1Values, referenceMean, referenceSd, maximumAbsoluteZ using the field table, then run the tool.
Read zScores, outlierIds. Interpret flags, units, ordering and placeholder values using the rules below.
Review any reported issue or failed check, correct the supplied values when appropriate, and verify the result in its intended context.

Input field	Meaning	Value type and bounds	Requirement
sampleIds	Sample ids	list of string; each entry: string	Required
pc1Values	Pc 1 values	list of number; each entry: number	Required
referenceMean	Reference mean	number	Required
referenceSd	Reference sd	number	Required
maximumAbsoluteZ	Maximum absolute z	number	Required

Align sample IDs with PC1 values and require positive reference SD and nonnegative cutoff. Return all z scores and IDs strictly beyond the cutoff.^[1]

z = (PC1−referenceMean)/referenceSD; outlier if |z| > maximumAbsoluteZ

This summarizes the declared operation. Units, indexing, inclusivity and exceptional cases are explained in the surrounding text.

Output field	Meaning	Value type
zScores	Z scores	list of number
outlierIds	Outlier ids	list of string

json

{
  "input": {
    "sampleIds": [
      "A",
      "B",
      "C"
    ],
    "pc1Values": [
      0,
      1,
      5
    ],
    "referenceMean": 0,
    "referenceSd": 1,
    "maximumAbsoluteZ": 3
  },
  "output": {
    "zScores": [
      0,
      1,
      5
    ],
    "outlierIds": [
      "C"
    ]
  }
}

Limitations and assumptions

Only PC1 is checked. The tool does not run PCA or assign ancestry; threshold equality is retained.

The tool evaluates supplied observations or a declared model. It does not establish the biological cause of an observed pattern. Malformed requests produce input errors. A successfully evaluated request can still contain false flags, empty result lists or a result outside the supplied threshold; those outcomes have the meanings stated above.

Alternative or Complementary methods

Choose Population FST for this operation: Compute heterozygosity-based FST from population allele frequencies and explicit weights. For a complementary task, use Imputation Info Gate for this operation: Filter imputed variants by a caller-defined INFO-score floor.

The implementation reference documents the exact calculation, supported input shapes and returned fields.

References

Population PC Outliers — tool.io

Similar or alternative tools

Population FST
Compute heterozygosity-based FST from population allele frequencies and explicit weights.
Imputation Info Gate
Filter imputed variants by a caller-defined INFO-score floor.