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scAIDE: clustering of large-scale single-cell RNA-seq data reveals putative and rare cell types
Recent advancements in both single-cell RNA-sequencing technology and computational resources facilitate the study of cell types on global populations. Up to millions of cells can now be sequenced in one experiment; thus, accurate and efficient computational methods are needed to provide clustering...
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| 出版年: | NAR Genom Bioinform |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Oxford University Press
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7671411/ https://ncbi.nlm.nih.gov/pubmed/33575628 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/nargab/lqaa082 |
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