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SCAN-ATAC-Sim: a scalable and efficient method for simulating single-cell ATAC-seq data from bulk-tissue experiments
SUMMARY: scATAC-seq is a powerful approach for characterizing cell-type-specific regulatory landscapes. However, it is difficult to benchmark the performance of various scATAC-seq analysis techniques (such as clustering and deconvolution) without having a priori a known set of gold-standard cell typ...
Tallennettuna:
| Julkaisussa: | Bioinformatics |
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| Päätekijät: | , , , , , , , |
| Aineistotyyppi: | Artigo |
| Kieli: | Inglês |
| Julkaistu: |
Oxford University Press
2021
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| Aiheet: | |
| Linkit: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8289380/ https://ncbi.nlm.nih.gov/pubmed/33471102 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/bioinformatics/btaa1039 |
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