Scripts and data for the paper: Consequences and opportunities arising due to sparser single-cell RNA-seq datasets

Scripts and data for the paper: Consequences and opportunities arising due to sparser single-cell RNA-seq datasets<br>With the number of cells measured in single-cell RNA sequencing (scRNA-seq) datasets increasing exponentially and concurrent increased sparsity due to more zero counts being measured for many genes, we demonstrate here that downstream analyses on binary-based gene expression give similar results as count-based analyses. Moreover, a binary representation scales up to ~ 50-fold more cells that can be analyzed using the same computational resources. We also highlight the possibilities provided by binarized scRNA-seq data. Development of specialized tools for bit-aware implementations of downstream analytical tasks will enable a more fine-grained resolution of biological heterogeneity.本论文配套脚本与数据集：《单细胞RNA测序数据集稀疏化带来的影响与机遇》 随着单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）数据集的测序细胞数呈指数级增长，同时因众多基因的检测结果中零计数占比升高，数据集的稀疏性进一步加剧。本研究证实，基于二值化基因表达的下游分析，与基于原始计数的分析结果相似。 此外，在相同计算资源条件下，采用二值化表达形式可将可分析的细胞数量提升约50倍。 本研究同时探讨了二值化scRNA-seq数据所带来的应用潜力。 开发面向下游分析任务的比特感知实现专用工具，将能够实现对生物异质性更精细的解析。