Spike-In Scaling
Apply a spike-in normalization factor to sample signals.
Description
Spike-in scaling normalizes supplied signals to a reference spike-in count.
Spike-in scaling normalizes supplied signals to a reference spike-in count.1
Apply a spike-in normalization factor to sample signals.
When to use Spike-In Scaling
Use this tool to apply a spike-in normalization factor to sample signals.
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 Spike-In Scaling 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 referenceSpikeInReads, sampleSpikeInReads, sampleSignals using the field table and calculation rules, then run the tool.
- Read scalingFactor, scaledSignals, scaledSignalTotal. 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 |
|---|---|---|---|
| referenceSpikeInReads | Reference spike-in reads | number; minimum: 0 | Required |
| sampleSpikeInReads | Sample spike-in reads | number; minimum: 0 | Required |
| sampleSignals | Sample signals | list of number | Required |
Enter nonnegative reference, positive sample and finite signal list. Return factor, scaled values and sum; an empty list is allowed.
factor=reference/sample; scaled=signal×factor Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| scalingFactor | Spike-in scaling factor | number; minimum: 0 |
| scaledSignals | Scaled sample signals | list of number |
| scaledSignalTotal | Scaled signal total | number |
{
"input": {
"referenceSpikeInReads": 1000,
"sampleSpikeInReads": 500,
"sampleSignals": [
10,
20
]
},
"output": {
"scalingFactor": 2,
"scaledSignals": [
20,
40
],
"scaledSignalTotal": 60
}
}Limitations and assumptions
Signed signals are accepted. No spike-in measurement or protocol bias is corrected.
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.
Alternative or Complementary methods
Use Input Background Correction: Subtract input background from epigenomic sample signals. For a complementary task, use MeDIP Enrichment: Calculate MeDIP enrichment after volume normalization.
References
-
Spike-In Scaling — tool.io
Similar or alternative tools
- Input Background Correction
Subtract input background from epigenomic sample signals.
- MeDIP Enrichment
Calculate MeDIP enrichment after volume normalization.