bioRxivBioinformaticsPreprint
GraphMana: graph-native data management for population genomics projects
Ehsan EstajiiD, Shiwei ZhaoiD, Zhao-Yang Chen, Shuai Nie, Jian‐Feng MaoiD
Abstract
Population genomics projects rely on fragmented file-based workflows that lose provenance and require full reprocessing when samples are added. Graph-Mana stores variant data in a graph database as packed genotype arrays with pre-computed population statistics, enabling incremental sample addition, provenance tracking, cohort management, and export to 17 formats. Two access paths serve different needs: a FAST PATH reading population-level arrays in O(K) time and a FULL PATH unpacking per-sample genotypes in O(N) time. On human 1000 Genomes data (3,202 samples, 70.7M variants), Graph-Mana completed a 46-operation lifecycle in 98 minutes from a single persistent database.
- organism: human
- assay: whole-genome sequencing
- research focus: variant calling
- research focus: database / resource
- research focus: benchmarking
- approach: graph neural network
- approach: statistical model
- Citations
- 0
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