Combat Location Scale

Recenter and rescale batch samples using caller-estimated location and scale parameters.

Description

Location-scale adjustment maps a batch's supplied mean and SD to pooled reference values.

Location-scale adjustment maps a batch's supplied mean and SD to pooled reference values. Applying those parameters is distinct from estimating them with ComBat's model.^[1]

Recenter and rescale batch samples using caller-estimated location and scale parameters.

When to use Combat Location Scale

Use this tool to recenter and rescale batch samples using caller-estimated location and scale parameters.

Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.

How to use Combat Location Scale and understand its results

Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.
Enter sampleValues, batchMean, batchStandardDeviation, pooledMean, pooledStandardDeviation using the field table and calculation rules, then run the tool.
Read adjustedValues, batchMeanShift. 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
sampleValues	Sample values	list of number	Required
batchMean	Batch mean	number	Required
batchStandardDeviation	Batch standard deviation	number	Required
pooledMean	Pooled mean	number	Required
pooledStandardDeviation	Pooled standard deviation	number	Required

Provide finite sample values and means with strictly positive batch/pooled SD. Adjust every value and return the resulting list plus pooled-minus-batch mean shift. An empty sample list is allowed and returns an empty list.

adjusted=(sample−batchMean)/batchSD×pooledSD+pooledMean

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

Output field	Meaning	Value type
adjustedValues	Adjusted values	list of number
batchMeanShift	Batch mean shift	number

json

{
  "input": {
    "sampleValues": [
      10,
      12
    ],
    "batchMean": 11,
    "batchStandardDeviation": 1,
    "pooledMean": 20,
    "pooledStandardDeviation": 2
  },
  "output": {
    "adjustedValues": [
      18,
      22
    ],
    "batchMeanShift": 9
  }
}

Limitations and assumptions

No empirical-Bayes parameter estimation, covariate model or biological-effect preservation is implemented. Incorrect upstream parameters can remove real signal; this is not a full ComBat workflow.

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.

Alternative or Complementary methods

Use Batch Effect Screen: Screen batch-level mean shifts relative to within-batch variation. For a complementary task, use Expression Zscore: Map standardized expression to a clipped diverging-color coordinate.

References

Combat Location Scale — tool.io

Similar or alternative tools

Batch Effect Screen
Screen batch-level mean shifts relative to within-batch variation.
Expression Zscore
Map standardized expression to a clipped diverging-color coordinate.