--- id: "claim:normalization-for-sampled-count-data-2026-06-22-biorxiv-v4:13c4a8cca384aa4221fb" kind: "claim" title: "Dense representations can make analyses of millions or tens of millions of cells problematic or intractable." description: "" url: "https://sina.bio/claim/dense-representations-can-make-analyses-of-millions-or-tens-of-millions-098aceed" --- # Dense representations can make analyses of millions or tens of millions of cells problematic or intractable. ## Content Dense representations can make analyses of millions or tens of millions of cells problematic or intractable. ## Metadata ```json { "claim_position": 118, "source_publication_id": "version:normalization-for-sampled-count-data--2026-06-22-biorxiv-v4", "source_work_id": "work:normalization-for-sampled-count-data" } ``` ## Connections (4) ### GPU-accelerated single-cell analysis at scale with rapids-singlecell - ID: `publication:doi:10.48550/arxiv.2603.02402` - Kind: `publication` - Direction: `outgoing` - URL: This publication is cited in support of this claim. > Such dense or memory-intensive representations > can lead to significant analysis limitations in large scRNA-seq > workflows (Borella et al., 2021), and can slow downstream > computations enough to make million- or tens-of-millions-cell > analyses problematic or intractable (Dicks et al., 2026). Source: 2026-06-22-biorxiv-v4.pdf — ### Normalization for sampled count data - ID: `version:normalization-for-sampled-count-data--2026-06-22-biorxiv-v4` - Kind: `publication` - Direction: `incoming` - URL: This publication contains this grounded claim. > Such dense or memory-intensive representations can lead to significant analysis limitations in large scRNA-seq workflows (Borella et al., 2021), and can slow downstream computations enough to make million- or tens-of-millions-cell analyses problematic or intractable (Dicks et al., 2026). Source: 2026-06-22-biorxiv-v4.pdf — ### PsiNorm: a scalable normalization for single-cell RNA-seq data - ID: `publication:doi:10.1093/bioinformatics/btab641` - Kind: `publication` - Direction: `outgoing` - URL: This publication is cited in support of this claim. > Such dense or memory-intensive representations > can lead to significant analysis limitations in large scRNA-seq > workflows (Borella et al., 2021), and can slow downstream > computations enough to make million- or tens-of-millions-cell > analyses problematic or intractable (Dicks et al., 2026). Source: 2026-06-22-biorxiv-v4.pdf — ### Pearson residuals are nonmonotonic and typically dense, making analyses of millions or tens of millions of cells problem - ID: `result:normalization-for-sampled-count-data-2026-06-22-biorxiv-v4:32a8f39730fa48b40b10` - Kind: `result` - Direction: `incoming` - URL: This claim supports this result.