CRISPR Off-Target Count
Count CRISPR epigenome-editing off-targets by mismatch risk threshold.
Description
Mismatch count is one dimension of CRISPR candidate off-target review.
Mismatch count is one dimension of CRISPR candidate off-target review.1
Count CRISPR epigenome-editing off-targets by mismatch risk threshold.
When to use CRISPR Off-Target Count
Use this tool to count CRISPR epigenome-editing off-targets by mismatch risk threshold.
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 CRISPR Off-Target Count 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 offTargetMismatchCounts, maximumRiskMismatchCount using the field table and calculation rules, then run the tool.
- Read offTargetCount, highRiskOffTargetCount, minimumMismatchCount, highRiskOffTargetPresent. 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 |
|---|---|---|---|
| offTargetMismatchCounts | Off-target mismatch counts | list of number | Required |
| maximumRiskMismatchCount | Maximum risky mismatch count | integer; minimum: 0 | Required |
Enter nonempty nonnegative integer counts and nonnegative integer maximum. Return qualifying count, minimum and any-risk flag.
highRisk=count(mismatches≤maximum) Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| offTargetCount | Off-target count | integer; minimum: 0 |
| highRiskOffTargetCount | High-risk off-target count | integer; minimum: 0 |
| minimumMismatchCount | Minimum mismatch count | integer; minimum: 0 |
| highRiskOffTargetPresent | High-risk off-target present | boolean |
{
"input": {
"offTargetMismatchCounts": [
1,
3,
5,
2
],
"maximumRiskMismatchCount": 2
},
"output": {
"offTargetCount": 4,
"highRiskOffTargetCount": 2,
"minimumMismatchCount": 1,
"highRiskOffTargetPresent": true
}
}Limitations and assumptions
No alignments, PAMs, bulges or off-target effects are analyzed.
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 Motif Cluster: Count motif clusters using a maximum spacing. For a complementary task, use DNase Footprint Depth: Measure DNase footprint depth relative to flanks.
References
-
CRISPR Off-Target Count — tool.io
Similar or alternative tools
- Motif Cluster
Count motif clusters using a maximum spacing.
- DNase Footprint Depth
Measure DNase footprint depth relative to flanks.