ArticleMethods in molecular biology (Clifton, N.J.)2025
Single-Cell Transcriptomic Analysis of Normal and Malignant B Cells.
Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
1 citing paper in PubMed.
- GMIP: A Novel Prognostic Biomarker Influencing Immune Infiltration and Tumour Dynamics Across Cancer Types.Journal of cellular and molecular medicine · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In the past decade, single-cell (sc) transcriptomics has overcome the limitations of bulk analysis by measuring gene expression in individual cells, not just a population average. This can identify diverse cell types and states within a sample with high resolution, even without prior purification. Various technologies exist, each with its own capture, barcoding, and library preparation methods. This chapter focuses on the analysis of normal and malignant mature B cells using the 10× Genomics 5' sc-gene expression in parallel with B cell immune repertoire profiling. By integrating the gene expression data from similar cells, the complete transcriptome for each population can be reconstructed, while the identification of the expressed immunoglobulin genes allows investigating clonotype evolution and the detection of tumor clones that share the same clonally rearranged B cell receptor sequence. Researchers are guided through both the experimental protocols and data analysis with a comprehensive, step-by-step walkthrough of how to use some of the more popular single-cell software tools.
Indexed as
Identifiers
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Registered trials
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