পদ্ধতির তুলনা করুন
নির্বাচিত পদ্ধতিগুলো পাশাপাশি পর্যালোচনা করুন; যে সারিগুলোয় পার্থক্য আছে সেগুলো চিহ্নিত করা হয়।
| একক-কোষ মাইক্রোবায়োম বৈচিত্র্য বিশ্লেষণ× | মাল্টি-ওমিক্স মাইক্রোবায়োম ডাইভারসিটি অ্যানালাইসিস× | |
|---|---|---|
| ক্ষেত্র | জৈব তথ্যবিজ্ঞান | জৈব তথ্যবিজ্ঞান |
| পরিবার | Process / pipeline | Process / pipeline |
| উদ্ভবের বছর≠ | 2019-2022 | 2010s–present |
| প্রবর্তক≠ | Paul Blainey lab and Bhatt lab (pioneered microSPLiT and single-microbe genomics approaches) | Developed collectively; key frameworks by Le Cao et al. (mixOmics, 2017) and Argelaguet et al. (MOFA, 2018) |
| ধরন≠ | Computational-experimental omics pipeline | Integrative computational pipeline |
| মৌলিক উৎস≠ | 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 ↗ | Rohart, F., Gautier, B., Singh, A., & Le Cao, K.-A. (2017). mixOmics: An R package for 'omics feature selection and multiple data integration. PLOS Computational Biology, 13(11), e1005752. DOI ↗ |
| অপর নাম | sc-microbiome analysis, single-cell microbial profiling, single-bacterium sequencing, microSPLiT analysis | multi-omics microbiome profiling, integrated microbiome omics, multi-modal microbiome analysis, microbiome multi-omics integration |
| সম্পর্কিত≠ | 3 | 5 |
| সারসংক্ষেপ≠ | 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. | Multi-omics microbiome diversity analysis integrates two or more omic data layers — such as metagenomics, metatranscriptomics, metabolomics, and metaproteomics — to characterise both the composition and functional activity of microbial communities. By linking taxonomic diversity metrics with molecular phenotype data, the approach uncovers how community structure translates into ecological and host-relevant functions that no single omic layer can reveal alone. |
| ScholarGateডেটাসেট ↗ |
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