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| 단일 세포 미생물 군집 다양성 분석× | 단일 세포 변이 호출× | |
|---|---|---|
| 분야 | 생물정보학 | 생물정보학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2019-2022 | 2016 (Monovar; foundational single-cell SNV calling) |
| 창시자≠ | Paul Blainey lab and Bhatt lab (pioneered microSPLiT and single-microbe genomics approaches) | Hamim Zafar, Ken Chen, Nicholas Navin and colleagues |
| 유형≠ | Computational-experimental omics pipeline | Computational genomics pipeline |
| 원전≠ | Kehe, J., Kulesa, A., Ortiz, A., Ackerman, C. M., Thakku, S. G., Sellers, D., Bhatt, S., ... & Blainey, P. C. (2019). Massively parallel screening of synthetic microbial communities. Proceedings of the National Academy of Sciences, 116(26), 12804-12809. link ↗ | Zafar, H., Wang, Y., Nakhleh, L., Navin, N., & Chen, K. (2016). Monovar: single-nucleotide variant detection in single cells. Nature Methods, 13(6), 505–507. DOI ↗ |
| 별칭 | sc-microbiome analysis, single-cell microbial profiling, single-bacterium sequencing, microSPLiT analysis | scVariant calling, single-cell SNV calling, scDNA-seq variant detection, single-cell somatic mutation calling |
| 관련≠ | 3 | 1 |
| 요약≠ | Single-cell microbiome diversity analysis resolves the composition and functional heterogeneity of microbial communities at the level of individual cells or bacteria. By combining single-cell or single-bacterium isolation with high-throughput sequencing, this pipeline overcomes the averaging effect of bulk metagenomics, enabling detection of rare strains, intra-species variation, and cell-to-cell heterogeneity within complex microbiomes such as the gut, oral cavity, or environmental samples. | Single-cell variant calling is a bioinformatics pipeline that identifies DNA sequence variants — single-nucleotide variants (SNVs), small insertions and deletions, and copy-number alterations — within individual cells rather than across a bulk tissue mixture. By resolving the mutational landscape cell by cell, it reveals intra-tumoral heterogeneity, clonal architecture, and somatic mutation patterns that bulk sequencing obscures. The approach is central to cancer genomics, developmental biology, and any study where cell-to-cell genetic diversity is the primary question. |
| ScholarGate데이터셋 ↗ |
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