Dawnn benchmarking dataset: Simulated discrete clusters processing and label simulation

This project is a collection of files to allow users to reproduce the model development and benchmarking in "Dawnn: single-cell differential abundance with neural networks" (Hall and Castellano, under review). Dawnn is a tool for detecting differential abundance in single-cell RNAseq datasets. It is available as an R package here. Please contact us if you are unable to reproduce any of the analysis in our paper. The files in this collection correspond to the benchmarking dataset based on simulated discrete clusters. FILES: Data processing code adapted_discrete_clusters_sim_milo_paper.R Lightly adapted code from Dann et al. to simulate single-cell RNAseq datasets that form discrete clusters . generate_test_data_discrete_clusters_sim_milo_paper.R R code to assign simulated labels to datatsets generated from adapted_discrete_clusters_sim_milo_paper.R. Seurat objects saved as cells_sim_discerete_clusters_gex_seed_*.rds. Simulated labels saved as benchmark_dataset_sim_discrete_clusters.csv. Resulting datasets cells_sim_discerete_clusters_gex_seed_*.rds Seurat objects generated by generate_test_data_discrete_clusters_sim_milo_paper.R. benchmark_dataset_sim_discrete_clusters.csv Cell labels generated by generate_test_data_discrete_clusters_sim_milo_paper.R.

本项目提供一系列配套文件，以支持复现《Dawnn: single-cell differential abundance with neural networks》（Hall与Castellano，待审稿）中所述的模型开发与基准测试工作。Dawnn是一款用于检测单细胞RNA测序（single-cell RNAseq）数据集差异丰度的工具，可通过本项目提供的R包获取。若您无法复现论文中的任意分析内容，请与我们取得联系。本数据集集合中的文件均对应基于模拟离散聚类的基准测试数据集，具体文件说明如下：
1. 数据处理代码`adapted_discrete_clusters_sim_milo_paper.R`：该代码为轻量改编自Dann等人的研究代码，用于生成具有离散聚类结构的单细胞RNA测序模拟数据集。
2. `generate_test_data_discrete_clusters_sim_milo_paper.R`：用于为`adapted_discrete_clusters_sim_milo_paper.R`生成的数据集分配模拟标签的R代码。
3. 保存的Seurat对象：`cells_sim_discerete_clusters_gex_seed_*.rds`。
4. 保存的模拟标签文件：`benchmark_dataset_sim_discrete_clusters.csv`。
最终生成的数据集包括：
- `cells_sim_discerete_clusters_gex_seed_*.rds`：由`generate_test_data_discrete_clusters_sim_milo_paper.R`生成的Seurat对象。
- `benchmark_dataset_sim_discrete_clusters.csv`：由`generate_test_data_discrete_clusters_sim_milo_paper.R`生成的细胞标签文件。