Singel Cell Analysis FAQ
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• What Is the Spring Plot in Single-Cell Sequencing?
Single-cell sequencing is a powerful technique for analyzing gene expression at the resolution of individual cells, enabling the investigation of cellular heterogeneity and functional diversity within a population. In the context of single-cell data analysis, the SPRING plot serves as a visualization tool for representing the similarities and distinctions among cells. SPRING, short for “Scalable, PRecomputed Incremental Graph Layout,” employs a force-directed graph layout to project high-dimensional.......
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Single-cell sequencing data analysis does not necessarily require reliance on previously known marker genes for cell type identification. Nonetheless, known marker genes can greatly assist in identifying and interpreting the cellular composition within the dataset. In single-cell RNA sequencing (scRNA-seq) workflows, standard analytical steps include quality control, normalization, dimensionality reduction, clustering, and differential expression analysis—all of which can be performed independently of .....
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• What Are the Principles of Single-Cell Sequencing Using 10x Genomics Technology?
10x Genomics technology is a groundbreaking single-cell sequencing approach that enables the acquisition of genomic, transcriptomic, and epigenomic data at single-cell resolution. The principles of this technology comprise the following key steps: Preparation of Single-Cell Suspension Tissue or cell samples are enzymatically or mechanically dissociated into single-cell suspensions. Microdroplet Encapsulation The single-cell suspension is mixed with barcoded gel beads, each carrying a unique molecular......
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• What Is the Recommended Sample Number per Group for Single-Cell Sequencing Studies?
In single-cell sequencing experiments, determining the appropriate number of samples per group is essential for ensuring statistical power, biological interpretability, and data reproducibility. The following recommendations provide guidance based on study design considerations: Biological Replicates To ensure the statistical robustness and reproducibility of results, it is generally recommended to include 3–5 biological replicates per experimental group. Increasing the number of replicates can furt......
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• What Are the Key Concepts in Single-Cell Sequencing Analysis?
Single-cell sequencing is an advanced genomic technology that enables the profiling of gene expression at the resolution of individual cells, in contrast to conventional approaches that analyze bulk mixtures of many cells. This technique plays a critical role in elucidating cell-to-cell variability, characterizing tissue-level heterogeneity, and advancing research in developmental biology, oncology, immunology, and related fields. Technical Principles 1.Isolation of Individual Cells Individual cells......
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Single-cell sequencing has emerged as a transformative tool for investigating gene expression, transcriptional regulation, and related biological processes. Its strengths lie in resolving cellular heterogeneity, dissecting regulatory mechanisms, and driving advances in biomedical research. Revealing Cellular Heterogeneity Precisely resolve distinct cell subpopulations and delineate functional differences within complex tissues.Trace temporal cellular dynamics during development, differentiation, and stress
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• Can Single-Cell Sequencing Detect Genomic Abnormalities Such as Uniparental Disomy (UPD)?
Uniparental disomy (UPD) refers to the inheritance of two homologous chromosomes from a single parent, rather than one from each parent. This genomic abnormality may arise due to meiotic recombination errors, mitotic missegregation, or post-zygotic chromosomal rescue in aneuploid embryos. With the advancement of single-cell sequencing technologies, it has become feasible to detect and characterize UPD and other structural or allelic aberrations at the single-cell level by analyzing genomic data.The analytic
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• What Are the Recent Advances in Single-Cell Sequencing Technologies and Analytical Approaches?
Single-cell sequencing has emerged as a high-throughput genomic technique that enables comprehensive profiling of gene expression at single-cell resolution. Over the past years, significant progress has been achieved in this field, driven by advances in technology, data analysis, and multi-omics integration. The following outlines some of the major developments: Enhanced Resolution and Throughput Technological innovations have markedly improved the resolution and scalability of single-cell sequencin......
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• How Can Single-Cell Sequencing Be Performed on Non-Tumor Samples?
Non-tumor single-cell sequencing is a technique used to analyze individual cells from non-tumor samples in order to profile their transcriptomic and epigenomic characteristics under both physiological and pathological conditions. The general workflow for performing non-tumor single-cell sequencing includes the following steps: Cell Sample Preparation Obtain non-tumor cell samples, which may include specimens from blood, tissues, or organs. Sample collection and processing should adhere to rigorous l......
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• How to Address the Failure of Cell Clustering in Single-Cell Sequencing Data Analysis Using R?
When single-cell sequencing data fail to yield valid cell clustering results in R, potential causes may include low data quality, suboptimal parameter settings, or other technical factors. The following strategies can be considered to resolve this issue: Data Quality Control and Preprocessing Begin by performing thorough quality control and preprocessing. Assess the quality of raw data, filter out low-quality cells and poorly expressed genes, and apply appropriate normalization and transformation methods to
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