---
id: "claim:characterization-of-spatial-homogeneous-regions-in-tissues-with-concordex-2024-863f0517b0:76f68462f1662f03e118"
kind: "claim"
title: "k-nearest-neighbor graph representations of transcriptomics data are useful for evaluating spatial homogeneity."
description: ""
url: "https://sina.bio/claim/k-nearest-neighbor-graph-representations-of-transcriptomics-data-are-us-23404051"
---

# k-nearest-neighbor graph representations of transcriptomics data are useful for evaluating spatial homogeneity.

## Content

k-nearest-neighbor graph representations of transcriptomics data are useful for evaluating spatial homogeneity.

## Metadata

```json
{
  "claim_position": 37,
  "source_publication_id": "version:characterization-of-spatial-homogeneous-regions-in-tissues-with-concordex--2024-07-18-biorxiv-v2",
  "source_work_id": "work:characterization-of-spatial-homogeneous-regions-in-tissues-with-concordex"
}
```

## Connections (1)

### Quantitative assessment of single-cell RNA-seq clustering with CONCORDEX

- ID: `version:characterization-of-spatial-homogeneous-regions-in-tissues-with-concordex--2024-07-18-biorxiv-v2`
- Kind: `publication`
- Direction: `incoming`
- URL: <https://sina.bio/publication/quantitative-assessment-of-single-cell-rna-seq-clustering-with-concorde-2b6a4ccd>

This publication contains this grounded claim.

> We show that the kNN graph represen- tation of transcriptomics data is useful for answering ques- tions about spatial homogeneity in SRT data and develop an approach using spatial kNN graphs to identify SHRs.

Source: 2024-07-18-biorxiv-v2.pdf — <https://sina.bio/source/2024-07-18-biorxiv-v2-pdf>