How do you approach analyzing single-cell transcriptomic data to understand cellular diversity in the brain?

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Sample interview questions: How do you approach analyzing single-cell transcriptomic data to understand cellular diversity in the brain?

Sample answer:

1. Data Preparation and Preprocessing:

  • Accurately assess the quality of single-cell RNA-seq data using QC metrics and filtering techniques.
  • Normalize data to account for technical variations, such as library preparation and cell type composition.
  • Perform clustering and dimensionality reduction techniques to identify cell types and group cells with similar expression profiles.

2. Differential Gene Expression (DGE) Analysis:

  • Identify cells with significant differences in gene expression between conditions or cell types.
  • Apply appropriate statistical tests to determine the significance of these differences.
  • Functional annotation of differentially expressed genes using pathway analysis and enrichment analysis techniques.

3. Cell-Cell Communication Analysis:

  • Utilize methods to infer cell-to-cell interactions based on single-cell expression profiles.
  • Identify cell types with high connectivity and hub genes involved in signaling pathways.
  • Apply pseudotime analysis to study cell state transitions and dynamics.

4. Cell Trajectory and Lineage Analysis:

  • Construct cell-state maps to visualize the trajectory of cells along a developmental or disease progression axis.
  • Use pseudotime analysis to study cell differentiation, stem cell potency, and malignant transformation.
  • Integrate single-cell data with other omics data, such as epigenomics and proteomics, to gain a 360-degree view of cellular dynamics.

5. Multi-omics Integration and Joint Analysis:

  • Integrate single-cell transcriptomics data with other omics data (e.g., epigenomics, proteomics, and metabolomics) to gain a comprehensive view of cellular states and processes.
  • Use joint analysis techniques to identify cell types, pathways, and dynamic changes that are shared or unique to different omics platforms.

6. Single-cell Atlas C… Read full answer

Source: https://hireabo.com/job/2_3_37/Neuroscientist

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