Leading Edge Extractor
Extract the leading-edge subset around a running enrichment peak.
Description
An enrichment peak partitions an ordered gene list into a prefix or suffix.
An enrichment peak partitions an ordered gene list into a prefix or suffix. This helper extracts that segment and does not independently identify which genes belong to the tested set.1
Extract the leading-edge subset around a running enrichment peak.
When to use Leading Edge Extractor
Use this tool to extract the leading-edge subset around a running enrichment peak.
Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.
How to use Leading Edge Extractor and understand its results
- Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.
- Enter rankedGeneIds, peakIndex, enrichmentDirection using the field table and calculation rules, then run the tool.
- Read leadingEdgeGeneIds, leadingEdgeCount. 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 |
|---|---|---|---|
| rankedGeneIds | Ranked gene ids | list of string | Required |
| peakIndex | Peak index | number | Required |
| enrichmentDirection | Enrichment direction | string; one of "positive", "negative" | Required |
Enter nonempty ranked IDs, an in-range zero-based peak coordinate and positive or negative direction. Include the peak in either segment and return IDs/count. Use an integer coordinate: the schema accepts finite numbers and array slicing applies truncation if fractional.
positive: list[0..peakIndex]; negative: list[peakIndex..end] Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.
| Output field | Meaning | Value type |
|---|---|---|
| leadingEdgeGeneIds | Leading edge gene ids | list of string |
| leadingEdgeCount | Leading edge count | number |
{
"input": {
"rankedGeneIds": [
"a",
"b",
"c",
"d"
],
"peakIndex": 2,
"enrichmentDirection": "positive"
},
"output": {
"leadingEdgeGeneIds": [
"a",
"b",
"c"
],
"leadingEdgeCount": 3
}
}Limitations and assumptions
There is no gene-set membership input, so the returned segment can contain misses and is not automatically the standard GSEA leading-edge hit subset. Peak estimation occurs upstream.
Numeric inputs 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. Extremely large text inputs are rejected. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.
Alternative or Complementary methods
Use GSEA Running Sum: Compute a weighted GSEA running sum and its strongest excursion. For a complementary task, use Normalized Enrichment Score: Normalize enrichment against mean same-sign permutation magnitudes.
References
-
Leading Edge Extractor — tool.io
Similar or alternative tools
- GSEA Running Sum
Compute a weighted GSEA running sum and its strongest excursion.
- Normalized Enrichment Score
Normalize enrichment against mean same-sign permutation magnitudes.