Marker Expression Fraction

Summarize a marker dot plot’s detection share and mean expression.

Description

A marker dot plot often shows detected-cell share and mean expression separately.

A marker dot plot often shows detected-cell share and mean expression separately. The mean here includes every supplied cell, including zeros.^[1]

Summarize a marker dot plot’s detection share and mean expression.

When to use Marker Expression Fraction

Use this tool to summarize a marker dot plot’s detection share and mean expression.

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 Marker Expression Fraction 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 markerCounts, minimumDetectedCount using the field table and calculation rules, then run the tool.
Read detectedCells, expressionPercent, meanExpression. 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
markerCounts	Marker counts	list of number	Required
minimumDetectedCount	Minimum detected count	number	Required

Enter a nonempty nonnegative marker-count list and nonnegative detection threshold. Return detected count, percentage and mean expression. A zero threshold counts zero-valued cells as detected because comparison is inclusive.

detected=number of counts≥minimumDetected; percent=100 detected/n; mean=Σcounts/n

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

Output field	Meaning	Value type
detectedCells	Detected cells	number
expressionPercent	Expression percent	number
meanExpression	Mean expression	number

json

{
  "input": {
    "markerCounts": [
      0,
      2,
      4,
      0
    ],
    "minimumDetectedCount": 1
  },
  "output": {
    "detectedCells": 2,
    "expressionPercent": 50,
    "meanExpression": 1.5
  }
}

Limitations and assumptions

No library normalization, cluster grouping or marker specificity test is applied. The threshold is supplied and the mean is not restricted to detected cells.

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 UMI Matrix Sparsity: Measure sparsity of a cell-by-gene UMI count matrix. For a complementary task, use Cell Gene Count Filter: Filter single cells by detected gene-count threshold.

References

Marker Expression Fraction — tool.io

Similar or alternative tools

UMI Matrix Sparsity
Measure sparsity of a cell-by-gene UMI count matrix.
Cell Gene Count Filter
Filter single cells by detected gene-count threshold.