Related Experiment Video
Updated: Jun 11, 2025
07:41
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
8.9K
Exploring public cancer gene expression signatures across bulk, single-cell and spatial transcriptomics data with
Stefania Pirrotta1, Laura Masatti1, Anna Bortolato1
1Department of Biology, University of Padua, Padua 35121, Italy.
NAR Genomics and Bioinformatics
|October 4, 2024
Summary
Signifinder is a new R package that helps researchers analyze cancer gene expression data from bulk, single-cell, and spatial samples. It aids in understanding tumor complexity and improving cancer research.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Gene-expression signatures are vital for cancer research, aiding in mechanism understanding, subtype definition, prognosis prediction, and therapy efficacy assessment.
- Recent transcriptomic technologies like single-cell RNA sequencing and spatial transcriptomics reveal tumor cellular heterogeneity, requiring advanced computational tools.
Purpose of the Study:
- To introduce signifinder, a novel R Bioconductor package for analyzing cancer transcriptional signatures across diverse transcriptomic data types.
- To provide a streamlined framework for collecting and utilizing cancer signatures in bulk, single-cell, and spatial transcriptomics.
Main Methods:
- Implementation of signifinder as an R Bioconductor package.
- Leveraging publicly available, curated cancer transcriptional signatures.
- Demonstration of utility through three distinct case studies using bulk, single-cell, and spatial transcriptomic data.
Main Results:
- Signifinder facilitates the assessment of tumor characteristics, including hallmark processes, therapy responses, and tumor microenvironment features.
- Case studies illustrate the application and insights gained from transcriptional signatures in various high-resolution transcriptomic analyses.
- The package enables cell-resolution transcriptional signature analysis in oncology.
Conclusions:
- Signifinder offers a comprehensive framework for interpreting high-resolution cancer transcriptomic data.
- The package addresses the complexity of tumor heterogeneity and advances cancer data analysis.
- It enhances the utility of transcriptional signatures in understanding cancer biology and improving patient outcomes.
