GCSA2
基于广义压缩后缀数组的图索引方法，将变异图上的所有路径编码为可搜索的 索引结构，支持高效的 k-mer 搜索和精确匹配。该方法是 VG 工具包的核心 索引引擎。
| Property | Value |
|---|---|
| Purpose | 变异图的高效 k-mer 索引 |
| Time Complexity | O(n) |
| Space Complexity | O(n) |
| Year | 2017 |
| Difficulty | Advanced |
| Languages | C++ |
| Category | Graph Genomics |
Complexity Analysis
- Time Complexity:
O(n) - Space Complexity:
O(n)
Performance Insight: The time complexity of this algorithm is linear (O(n)), scales linearly to TB-scale data and is suitable for streaming pipelines. Linear space can often be reduced by constant factors via sliding-window techniques.
Note: Complexity analysis is based on theoretical models. Actual runtime is affected by input scale, hardware, and implementation optimizations. Benchmark for your specific workload.
Literature & Implementation
Related Tools
VG · Minigraph · GraphAligner