Pith Number

pith:5JNBDJVA

pith:2026:5JNBDJVAYJRMWTUBFO7YO4C7DW

not attested not anchored not stored refs resolved

scShapeBench: Discovering geometry from high dimensional scRNAseq data

Andrew J Steindl, Brian Tshilengi Di Bassinga, C\'esar Miguel Valdez C\'ordova, Christine L Chaffer, Daniel Neumann, Dhananjay Bhaskar, Guy Wolf, Ihuan Gunawan, Jo\~ao Felipe Rocha, John G Lock, Leire Torices, Matthew Scicluna, Shabarni Gupta, Smita Krishnaswamy, Timothy J. Mann, Zachary Warren

scReebTower extracts Reeb graphs from diffusion geometry to classify single-cell data shapes more accurately than PAGA or Mapper.

arxiv:2605.12662 v1 · 2026-05-12 · cs.LG · q-bio.GN

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\usepackage{pith}
\pithnumber{5JNBDJVAYJRMWTUBFO7YO4C7DW}

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Record completeness

1 Bitcoin timestamp

2 Internet Archive

3 Author claim open · sign in to claim

4 Citations open

5 Replications open

✓ Portable graph bundle live · download bundle · merged state

The bundle contains the canonical record plus signed events. A mirror can host it anywhere and recompute the same current state with the deterministic merge algorithm.

Claims

C1strongest claim

Our results indicate that scReebTower outperforms existing baselines.

C2weakest assumption

Expert annotations of real single-cell datasets into the four discrete shape categories are accurate, consistent, and sufficient to represent the geometries that matter for downstream analysis.

C3one line summary

scShapeBench supplies synthetic and real annotated single-cell datasets across four shape categories, with scReebTower outperforming PAGA and Mapper on topology-aware metrics.

References

31 extracted · 31 resolved · 2 Pith anchors

[1] Spatial reconstruction of single-cell gene expression data.Nat Biotechnol, 33(5):495–502, April 2015 2015

[2] The single-cell transcriptional landscape of mammalian organogenesis.Nature, 566(7745):496–502, February 2019 2019

[3] Visualization and cellular hierarchy inference of single-cell data using spade.Nature protocols, 11(7):1264–1279, 2016 2016

[4] Guillaume Huguet, D. S. Magruder, Alexander Tong, Oluwadamilola Fasina, Manik Kuchroo, Guy Wolf, and Smita Krishnaswamy. Manifold interpolating optimal-transport flows for trajectory inference, 2022 2022

[5] Trajecto- rynet: A dynamic optimal transport network for modeling cellular dynamics 2020

Formal links

2 machine-checked theorem links

Receipt and verification

First computed	2026-05-18T03:09:50.481058Z
Builder	pith-number-builder-2026-05-17-v1
Signature	Pith Ed25519 (`pith-v1-2026-05`) · public key
Schema	pith-number/v1.0

Canonical hash

ea5a11a6a0c262cb4e812bbf87705f1dbc02b6ba5ef160d8f2c1acd46dfa13d4

Aliases

arxiv: 2605.12662 · arxiv_version: 2605.12662v1 · doi: 10.48550/arxiv.2605.12662 · pith_short_12: 5JNBDJVAYJRM · pith_short_16: 5JNBDJVAYJRMWTUB · pith_short_8: 5JNBDJVA

Agent API

Resolver JSON Graph JSON Events JSON Schema Signing key

Verify this Pith Number yourself

curl -sH 'Accept: application/ld+json' https://pith.science/pith/5JNBDJVAYJRMWTUBFO7YO4C7DW \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ea5a11a6a0c262cb4e812bbf87705f1dbc02b6ba5ef160d8f2c1acd46dfa13d4

Canonical record JSON

{
  "metadata": {
    "abstract_canon_sha256": "57d424d82ca020f90cd9c0952c28bc833629e09898cd4b4d801978e59b6a30d0",
    "cross_cats_sorted": [
      "q-bio.GN"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "primary_cat": "cs.LG",
    "submitted_at": "2026-05-12T19:10:38Z",
    "title_canon_sha256": "5df443858ca61960a0c481d5dd73f87edb83f646b9a406d2b9ccfca0f334e02f"
  },
  "schema_version": "1.0",
  "source": {
    "id": "2605.12662",
    "kind": "arxiv",
    "version": 1
  }
}