Article

scBSP: A fast and accurate tool for identifying spatially variable features from high-resolution spatial omics data

2025-02-07

Abstract excerpt

<h4>ABSTRACT</h4> Emerging spatial omics technologies empower comprehensive exploration of biological systems from multi-omics perspectives in their native tissue location in two and three- dimensional space. However, sparse sequencing capacity and growing spatial resolution in spatial omics present significant computational challenges in identifying biologically meaningful molecules that exhibit variable spatial...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 32afe465-0edb-5292-af5d-fe9c7d48604c
DOI: 10.1101/2025.02.02.636138

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

scBSP: A fast and accurate tool for identifying spatially variable features from high-resolution spatial omics dataDOI 10.1101/2025.02.02.636138Read

<i>DESpace2</i> : detection of differential spatial patterns in spatial omics dataSemantic proximity Read

SPEX: A modular end-to-end platform for high-plex tissue spatial omics analysisSemantic proximity Read

SM-Omics: An automated platform for high-throughput spatial multi-omicsSemantic proximity Read

Toward Computationally Complete Spatial OmicsSemantic proximity Read

Graph Fourier transform for spatial omics representation and analyses of complex organsSemantic proximity Read

Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystemSemantic proximity Read

Spatial omics for profiling the dynamic tumor microenvironmentSemantic proximity Read

SpaFun: Discovering Domain-specific Spatial Expression Patterns and New Disease-Relevant Genes using Functional Principal Component AnalysisSemantic proximity Read

GraphCompass: Spatial metrics for differential analyses of cell organization across conditionsSemantic proximity Read

Randomized Spatial PCA (RASP): a computationally efficient method for dimensionality reduction of high-resolution spatial transcriptomics dataSemantic proximity Read

Precise Characterization of Cellular States and Spatial Variable Patterns within Spatial TranscriptomicsSemantic proximity Read

<i>mosna</i> reveals different types of cellular interactions predictive of response to immunotherapies and survival in cancerSemantic proximity Read