Matrix Row Balance
Measure matrix row-sum balance by coefficient of variation.
Description
Contact-matrix row-sum balance can be summarized by relative dispersion.
Contact-matrix row-sum balance can be summarized by relative dispersion.1
Measure matrix row-sum balance by coefficient of variation.
When to use Matrix Row Balance
Use this tool to measure matrix row-sum balance by coefficient of variation.
Prepare the already measured signals, counts, coordinates, fitted coefficients or sequence strings requested. Keep assay definitions, units, aligned lists and caller-selected thresholds consistent.
How to use Matrix Row Balance and understand its results
- Prepare the already measured signals, counts, coordinates, fitted coefficients or sequence strings requested. Keep assay definitions, units, aligned lists and caller-selected thresholds consistent.
- Enter matrixRowSums, maximumCvPercent using the field table and calculation rules, then run the tool.
- Read meanRowSum, rowSumCvPercent, balanced. 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 |
|---|---|---|---|
| matrixRowSums | Matrix row sums | list of number | Required |
| maximumCvPercent | Maximum coefficient of variation | number; minimum: 0 | Required |
Enter nonempty nonnegative row sums with positive mean and nonnegative CV maximum. Return mean/CV/inclusive gate.
CV%=100populationSD(rowSums)/mean(rowSums) Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| meanRowSum | Mean row sum | number; minimum: 0 |
| rowSumCvPercent | Row-sum coefficient of variation | number; minimum: 0 |
| balanced | Within supplied CV limit | boolean |
{
"input": {
"matrixRowSums": [
90,
100,
110
],
"maximumCvPercent": 10
},
"output": {
"meanRowSum": 100,
"rowSumCvPercent": 8.16496580927726,
"balanced": true
}
}Limitations and assumptions
No matrix balancing or contact-quality verdict is performed.
Numeric inputs, where present, 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 ICE Convergence Round: Find the first ICE correction round meeting a convergence tolerance. For a complementary task, use Insulation Local Minimum: Find the lowest insulation score within an interior search range.
References
-
Matrix Row Balance — tool.io
Similar or alternative tools
- ICE Convergence Round
Find the first ICE correction round meeting a convergence tolerance.
- Insulation Local Minimum
Find the lowest insulation score within an interior search range.