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science
machine-learning
الضمانة 75%

الخلاصة

Comparison and evaluation of statistical error models for scRNA-seq BACKGROUND: Heterogeneity in single-cell RNA-seq (scRNA-seq) data is driven by multiple sources, including biological variation in cellular state as well as technical variation introduced during experimental processing. Deconvolving these effects is a key challenge for preprocessing workflows. Recent work has demonstrated the importance and utility of count models for scRNA-seq analysis, but there is a lack of consensus on whic...

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