Beyond benchmarking: towards predictive models of dataset-specific single-cell RNA-seq pipeline performance

This repository includes: clusters.zip .Once unzipped, the top-level directory is named clusters/. Within this directory, there are 86 sub-directories, one for each of the scRNA-seq datasets used in the paper. These sub-directories are named with the corresponding EBI Single Cell Atlas IDs. Each sub-directory contains CSV files containing clustering results for each of the pipelines run on that dataset. *_unscaled.csv CSV files containing raw performance metrics (CH, DB, SIL, GSEA) computed on each pipeline and dataset combination *CorrectedImputed.csv and gseaScaledImputed.csv CSV files containing performance metrics corrected for the number of clusters and missing values imputed in the case of CH, SIL, and DB. For GSEA, only scaling and imputation was performed. pipelineParams.csv and datasetFeatures.csv CSV files containing parameters used for each of the pipelines run, and dataset summary statistics for each of the scRNA-seq datasets.本仓库包含以下内容： clusters.zip。 解压后，顶层目录名为clusters/。 该目录下共有86个子目录，分别对应论文中使用的每一项单细胞RNA测序（scRNA-seq）数据集，子目录以对应的欧洲生物信息研究所（European Bioinformatics Institute, EBI）单细胞图谱ID命名。 每个子目录均包含对应数据集上各分析流程的聚类结果CSV文件： *_unscaled.csv：包含针对各分析流程与数据集组合计算得到的原始性能指标（CH、DB、SIL、GSEA）的CSV文件。 *CorrectedImputed.csv 与 gseaScaledImputed.csv：包含针对聚类数目校正且针对缺失值进行插补后的性能指标CSV文件，其中CH、SIL、DB指标同时完成校正与插补，GSEA指标仅进行缩放与插补。 pipelineParams.csv 与 datasetFeatures.csv：分别包含各分析流程所用参数，以及各项单细胞RNA测序数据集的汇总统计量的CSV文件。