CPG Island Window Scan
Classify DNA windows by GC fraction and CpG observed/expected ratio using caller criteria.
Description
CpG-rich windows can be screened using GC composition and a CpG observed/expected ratio.
CpG-rich windows can be screened using GC composition and a CpG observed/expected ratio. Window length and thresholds define the selected profile.
Classify DNA windows by GC fraction and CpG observed/expected ratio using caller criteria.
When to use CPG Island Window Scan
Use this for the following task: Classify DNA windows by GC fraction and CpG observed/expected ratio using caller criteria.
Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
How to use CPG Island Window Scan and understand its results
- Prepare the observed records or explicit model parameters requested below. Keep probabilities as fractions and paired records aligned.
- Enter sequence, windowLength, stepLength, minimumGcFraction, minimumObservedExpected using the field table, then run the tool.
- Read windowStarts, gcFractions, cpgObservedExpected, islandStarts. 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 |
|---|---|---|---|
| sequence | Sequence | string | Required |
| windowLength | Window length | integer | Required |
| stepLength | Step length | integer | Required |
| minimumGcFraction | Minimum gc fraction | number | Required |
| minimumObservedExpected | Minimum observed expected | number | Required |
Normalize canonical DNA and scan full windows at positive steps. Count C, G and adjacent CG pairs; return zero-based starts satisfying both inclusive thresholds.1
GC=(C+G)/L; CpG O/E=CpGcount×L/(C×G), or 0 when C×G=0 This summarizes the declared operation. Units, indexing, inclusivity and exceptional cases are explained in the surrounding text.
| Output field | Meaning | Value type |
|---|---|---|
| windowStarts | Window starts | list of number |
| gcFractions | Gc fractions | list of number |
| cpgObservedExpected | Cpg observed expected | list of number |
| islandStarts | Island starts | list of number |
{
"input": {
"sequence": "CGCGAAAA",
"windowLength": 4,
"stepLength": 4,
"minimumGcFraction": 0.5,
"minimumObservedExpected": 0.6
},
"output": {
"windowStarts": [
0,
4
],
"gcFractions": [
1,
0
],
"cpgObservedExpected": [
2,
0
],
"islandStarts": [
0
]
}
}Limitations and assumptions
Windows are not merged into islands. Criteria are supplied and no methylation or regulatory activity is inferred; comparison limits apply.
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 Sliding GC Content for this operation: Calculate GC content in complete DNA windows at a chosen step size. For a complementary task, use GC Skew for this operation: Calculate GC skew and compositional bias without inferring replication strand from skew alone.
The implementation reference documents the exact calculation, supported input shapes and returned fields.
References
-
CPG Island Window Scan — tool.io
Similar or alternative tools
- Sliding GC Content
Calculate GC content in complete DNA windows at a chosen step size.
- GC Skew
Calculate GC skew and compositional bias without inferring replication strand from skew alone.