Comparison of bias and resolvability in single-cell and single-transcript methods
Rammohan et al. propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is defined and compared between methods. Their framework provides a practical solution for benchmarking and comparing the performance of any method, ill...
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| Autores principales: | , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/18b4195254e744b8911081408a581ce2 |
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| Sumario: | Rammohan et al. propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is defined and compared between methods. Their framework provides a practical solution for benchmarking and comparing the performance of any method, illustrated by analysing single-cell and single-transcript methods. |
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