CTCF Orientation

Classify a CTCF motif pair as convergent, divergent, or tandem.

Description

CTCF motif pairs have convergent, divergent or tandem orientations.

CTCF motif pairs have convergent, divergent or tandem orientations.^[1]

Classify a CTCF motif pair as convergent, divergent, or tandem.

When to use CTCF Orientation

Use this tool to classify a CTCF motif pair as convergent, divergent, or tandem.

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 CTCF Orientation 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 leftMotifOrientation, rightMotifOrientation using the field table and calculation rules, then run the tool.
Read pairClass, convergent. 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
leftMotifOrientation	Left motif orientation	string; one of "forward", "reverse"	Required
rightMotifOrientation	Right motif orientation	string; one of "forward", "reverse"	Required

Select exact orientation enums; return classification.

forward/reverse→convergent; reverse/forward→divergent; equal→tandem

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

Output field	Meaning	Value type
pairClass	Orientation class	string; one of "convergent", "divergent", "tandem"
convergent	Convergent pair	boolean

json

{
  "input": {
    "leftMotifOrientation": "forward",
    "rightMotifOrientation": "reverse"
  },
  "output": {
    "pairClass": "convergent",
    "convergent": true
  }
}

Limitations and assumptions

No motifs, binding or chromatin loop is detected.

Numeric inputs, where present, must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Extremely large text inputs are rejected. 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 TAD Boundary Distance: Measure adjacent TAD boundary distances. For a complementary task, use ABC Linkage Rank: Rank enhancer-gene links by activity-by-contact score.

References

CTCF Orientation — tool.io

Similar or alternative tools

TAD Boundary Distance
Measure adjacent TAD boundary distances.
ABC Linkage Rank
Rank enhancer-gene links by activity-by-contact score.