Spider: a flexible and unified framework for simulating spatial transcriptomics data.

ABSTRACT:

Motivation

Spatial transcriptomics (ST) technologies provide valuable insights into cellular heterogeneity by simultaneously acquiring both gene expression profiles and cellular location information. However, the limited diversity and accuracy of "gold standard" datasets hindered the effectiveness and fairness of benchmarking rapidly growing ST analysis tools.

Results

To address this issue, we proposed Spider, a flexible and comprehensive framework for simulating ST data without requiring real ST data as a reference. By characterizing the spatial patterns using cell type proportions and transition matrix between adjacent cells, Spider can produce more realistic and diverse simulated data and offer enhanced modeling flexibility compared to existing simulation methods. Additio

SUBMITTER: Yang J 

PROVIDER: S-EPMC12790819 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature