Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Search research articles

Related Experiment Video

Updated: May 9, 2026

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Protocol to decipher complex spatial transcriptomics data using STMiner.

Peisen Sun¹, Mingxuan Li¹, Kai Ye²

¹School of Automation Science and Engineering, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China; MOE Key Lab for Intelligent Networks & Networks Security, Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an, China.

|May 24, 2025

Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Mirrored structural symmetry index (VMSSI): a novel approach for diagnosing MR-negative focal cortical dysplasia using structural MRI.

Frontiers in neuroscience·2026

Same author

A mechanism-inspired integrated dual-frequency ultrasound transducer for cavitation-enhanced transdermal drug delivery.

Biomaterials·2026

Same author

Effect of chitosan and ε-Polylysine composite coating on postharvest quality maintenance and disease resistance of fresh <i>Tremella fuciformis</i>.

Food chemistry: X·2026

Same author

A novel glycolipid composite index predicting cardiovascular disease in Chinese adults with abnormal glucose metabolism: a nationwide cohort study.

Frontiers in cardiovascular medicine·2026

Same author

AND-logic amplification enables one-pot co-detection of extracellular vesicle miRNA and APE1.

Analytical biochemistry·2026

Same author

Giant Well-Differentiated Liposarcoma in the Retroperitoneal Space.

Journal of the College of Physicians and Surgeons--Pakistan : JCPSP·2026

Same journal

Computational protocol for modeling supported nanoparticle catalysts with strong metal-support interactions.

STAR protocols·2026

Same journal

Protocol for genomic mapping of chromatin targets using high-throughput CUT&RUN.

STAR protocols·2026

Same journal

A protocol for noninvasive quantification of dietary fat absorption in mice.

STAR protocols·2026

Same journal

Protocol for an AlCl<sub>3</sub>-induced Alzheimer's model in zebrafish larvae with optimized pH and behavioral assessment.

STAR protocols·2026

Same journal

Protocol for live cell barcoding and immunophenotyping of human hematological malignancies using cytometry by time of flight.

STAR protocols·2026

Same journal

Generating drug resistance models in human and murine cancer cell lines and assessing cross-resistance to chemotherapeutics and KRAS inhibitors.

STAR protocols·2026

See all related articles

This summary is machine-generated.

This study introduces STMiner, a new protocol for analyzing complex spatial transcriptomics data. It simplifies the process of identifying gene expression patterns within tissues, overcoming common data challenges.

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

Spatial transcriptomics (ST) data analysis presents challenges including uneven sampling, sparsity, and unclear tissue boundaries.
Existing methods may struggle with the complexity and heterogeneity inherent in ST datasets.

Purpose of the Study:

To present a user-friendly protocol for deciphering complex spatial transcriptomics data.
To enable researchers to effectively analyze ST data without requiring additional reference datasets.

Main Methods:

The protocol details the installation and usage of STMiner, a software tool for ST data analysis.
Key steps include loading ST data, identifying spatially variable genes, and determining gene sets associated with specific tissue structures.

Keywords:

Bioinformatics Gene Expression Genomics RNAseq Systems biology

More Related Videos

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Related Experiment Videos

Last Updated: May 9, 2026

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Mapping the Structure-Function Relationships of Disordered Oncogenic Transcription Factors Using Transcriptomic Analysis

Published on: June 27, 2020

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Comprehensive Spatial Profiling of Species-agnostic Transcriptomes via Stereo-seq

Published on: October 31, 2025

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Mining Spatial Transcriptomics Datasets using DeepSpaceDB

Published on: September 5, 2025

Main Results:

STMiner facilitates the identification of spatial expression patterns within complex ST data.
The protocol is adaptable to various ST data resolutions and platforms.

Conclusions:

STMiner provides a robust and versatile solution for analyzing complex spatial transcriptomics data.
This protocol empowers researchers to explore spatial gene expression with greater ease and accuracy.