Year: 2026
Type: preprint
Abstract: Updating a graph by inserting or replacing nodes while preserving semantics and reusing existing structure is a recurring computational problem. In population genetics, this problem arises in the genotype representation graph (GRG), a directed acyclic graph that losslessly encodes phased genetic variation across hundreds of thousands of samples by sharing subgraph structure for individual mutations. In a GRG, each mutation's carrier set is implicitly encoded as the set of leaf nodes reachable from the node it is assigned to. Updating a mutation is therefore a structural editing problem, and current approaches remap mutations individually. This paper introduces a batched mutation-remapping algorithm that replaces independent reuse-aware traversals with a single shared reverse-topological pass, identifying reuse candidates for an entire batch at once. The pass propagates compact bit-parallel per-mutation state and uses an adaptive sparse/dense carrier set representation spanning rare-to-common variant densities. Batching is the memory-scalable complement to split-based parallelism, which instead replicates graph and traversal state per worker. Our remapping is evaluated on a controlled update workload and on end-to-end allele polarization, a bulk carrier set update that is common in population genetic analysis. Our approach is up to 10.5$\times$ faster than independent remapping while preserving exact carrier-set semantics.
Source: arXiv (Cornell University)
Authors: Li, Aaron, Li, Yifan, DeHaas, Drew, Guidi, Giulia
Institution: Cornell University
Topic: Graph Theory and Algorithms
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G122673668, G1286236842, G1353381076, G1453181110, G1503004319, G1677143136, G1799333409, G1863003419, Track 4: Advanced CI Coordination Ecosystem: Monitoring and Measurement Services, G298330452, G3083819904, G3136028036, G34258105, G3562386289, G382641700, G3927959030, G3993056153, Track 1: ACCESS Resource Allocations Marketplace and Platform Services (RAMPS), G4010157413, G419881185, G4275568664, G42916606, G4403015908, G4501827968, G4590904221, ACO: An Open CI Ecosystem to Advance Scientific Discovery (OpenCI), G498139845, G5076365615, Track 3: COre National Ecosystem for CyberinfrasTructure (CONECT), G5098925467, G5156331529, G5367127336, G5464919783, G6247045938, ACED: Fast and Scalable Whole Genome Analysis on Emerging Hardware Technologies, G6652958823, G7526614437, G754761654, G8108599699, Track 2: Customized Multi-tier Assistance, Training, and Computational Help (MATCH) for End User ACCESS to CI, G8499740153, G969889393
OpenAlex ID: W7204596774
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