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将生物大模型、对接计算引擎与组学管线并排横向对比。按获取方式、硬件开销及细分领域灵活筛选，在一分钟内得出客观可辩护的技术选型方案。
| 技术参数指标 | ＋ 添加工具 | |||||
|---|---|---|---|---|---|---|
| Category | Single-Cell & Spatial Biology | Single-cell, Spatial & Cytometry | Single-cell, Spatial & Cytometry | Single-cell, Spatial & Cytometry | Single-cell, Spatial & Cytometry | — |
| Subcategory | Single-Cell Atlas Mapping | Conventional or Statistical Baselines | Conventional or Statistical Baselines | Conventional or Statistical Baselines | Conventional or Statistical Baselines | — |
| Company | Helmholtz Munich (Theis Lab) | Research / method authors | Research / method authors | Research / method authors | Research / method authors | — |
| Access mode | Open Source | Confirm distribution and exact release | Confirm distribution and exact release | Confirm distribution and exact release | Confirm distribution and exact release | — |
| Licence conditions | BSD-3-Clause | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | — |
| Compute requirements | 1x GPU (CUDA-enabled) recommended | Version and data dependent | Version and data dependent | Version and data dependent | Version and data dependent | — |
| Biological application | Cell-type annotation, patient disease state mapping, and cell atlas expansion | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Research workflow | Query single-cell dataset -> map onto reference embedding -> transfer cell annotations | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Evidence level | Peer-reviewed research (Nature Biotechnology 2021) | OFFICIAL_DOCUMENTATION | PEER_REVIEWED_METHOD_OR_CONFERENCE | PEER_REVIEWED_METHOD_OR_CONFERENCE | PEER_REVIEWED_METHOD_OR_CONFERENCE | — |
| Commercial eligibility | Open source release | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | NOT_INDEPENDENTLY_AUDITED | — |
| Price | Free Open Source | Verify access and licence | Verify access and licence | Verify access and licence | Verify access and licence | — |
| Availability ⓘ | Available on GitHub and PyPI | Method paper or official documentation | Method paper or official documentation | Method paper or official documentation | Method paper or official documentation | — |
| Features | Architectural surgery updating reference neural networks with query-specific parameters, Preserves privacy and eliminates batch effects during cross-study integration, Extensible to scRNA-seq, scATAC-seq, and spatial transcriptomics datasets, Integrates with scvi-tools and Scanpy ecosystems | Azimuth (Seurat reference mapping) scientific method, Compatible single-cell expression matrix and named atlas reference, Anchor-based reference map and predicted cell labels | Baysor scientific method, Subcellular in-situ transcript positions and optional cell stain masks, Spatial transcript-informed cell boundaries | BBKNN scientific method, Single-cell latent-space representation and batch labels, Balanced neighbor graph for downstream analysis | CellRank scientific method, Single-cell trajectories, directional velocity or related transition kernels, Terminal state and fate probability hypotheses | — |
| Entry type | Open Source Software | Classical/statistical scientific method | Classical/statistical scientific method | Classical/statistical scientific method | Classical/statistical scientific method | — |
| AI role | Transfer Learning & Atlas Mapping | NON_AI_REFERENCE | NON_AI_STATISTICAL | NON_AI_STATISTICAL | NON_AI_STATISTICAL | — |
| Input data | 未明确记录 | Compatible single-cell expression matrix and named atlas reference | Subcellular in-situ transcript positions and optional cell stain masks | Single-cell latent-space representation and batch labels | Single-cell trajectories, directional velocity or related transition kernels | — |
| Output data | 未明确记录 | Anchor-based reference map and predicted cell labels | Spatial transcript-informed cell boundaries | Balanced neighbor graph for downstream analysis | Terminal state and fate probability hypotheses | — |
| Validation | 未明确记录 | Published method scope; no independent BioAtlas execution or benchmark | Published method scope; no independent BioAtlas execution or benchmark | Published method scope; no independent BioAtlas execution or benchmark | Published method scope; no independent BioAtlas execution or benchmark | — |
| Type | Transfer learning framework for single-cell atlases | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Intended use | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Compatibility | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Manufacturer | Helmholtz Munich / Technical University of Munich | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Integration evidence | https://github.com/theislab/scarches | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |
| Laboratory handoff | Identifies novel aberrant disease cell states for targeted drug screening | 未明确记录 | 未明确记录 | 未明确记录 | 未明确记录 | — |