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Related Concept Videos

DNA Microarrays02:34

DNA Microarrays

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Microarrays are high-throughput and relatively inexpensive assays that can be automated to analyze large quantities of data at a time. They are used in genome-wide studies to compare gene or protein expression under two varied conditions, such as healthy and diseased states. Microarrays consist of glass or silica slides on which probe molecules are covalently attached through surface functionalization. Most commonly, the slides are prepared through the chemisorption of silanes to silica...
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Sequencing of the human genome has opened up several best-kept secrets of the genome. Scientists have identified thousands of genome variations that exist within a population. These variations can be a single nucleotide or a larger chromosomal variation.
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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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RNA-seq03:21

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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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DNA sequencing is a fundamental technique that is routinely used in the biological sciences. This method can be applied to a range of questions at different scales - from the sequencing of a cloned DNA fragment or the study of a mutation in a gene up to whole-genome sequencing. However, despite the widespread use of sequencing today, it was not until 1977 that Fredrick Sanger and his collaborators developed the chain-termination method to decode DNA sequences. It relies on the separation of a...
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Updated: Jun 30, 2025

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection
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Multi-slice spatial transcriptome domain analysis with SpaDo.

Bin Duan1,2,3,4, Shaoqi Chen5,6,7,8, Xiaojie Cheng5,6,7,8

  • 1State Key Laboratory of Cardiology and Medical Innovation Center, Shanghai East Hospital, Frontier Science Center for Stem Cell Research, Bioinformatics Department, School of Life Sciences and Technology, Tongji University, Shanghai, 200092, China. bioinfo_db@tongji.edu.cn.

Genome Biology
|March 20, 2024
PubMed
Summary
This summary is machine-generated.

SpaDo is a new tool for analyzing multiple spatial transcriptome slices, enabling deeper understanding of cellular landscapes. This approach integrates data from various sequencing platforms to uncover novel biological insights.

Keywords:
Multiple slice analysisSpatial domain detectionSpatial transcriptomics

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Area of Science:

  • Spatial transcriptomics
  • Computational biology
  • Bioinformatics

Background:

  • Advancements in spatial transcriptomics allow for the analysis of multiple tissue slices.
  • Integrating data from multiple slices is crucial for comprehensive spatial cellular landscape interpretation.

Purpose of the Study:

  • Introduce SpaDo, a novel computational tool for multi-slice spatial domain analysis.
  • Enable detection, annotation, and clustering of spatial domains across multiple tissue slices.

Main Methods:

  • SpaDo includes modules for multi-slice spatial domain detection and reference-based annotation.
  • The tool supports multiple slice clustering at both single-cell and spot resolutions.
  • Validated on over 40 multi-slice spatial transcriptome datasets from 7 sequencing platforms.

Main Results:

  • SpaDo effectively analyzes multi-slice spatial transcriptome data.
  • Demonstrated utility across diverse datasets and sequencing technologies.
  • Facilitates integrated analysis of spatial cellular heterogeneity.

Conclusions:

  • SpaDo is a versatile tool for multi-slice spatial domain analysis.
  • Offers potential for novel biological discoveries in spatial transcriptomics.
  • Enhances the interpretation of complex spatial cellular landscapes.