Inference of cell type-specific gene regulatory networks on cell lineages from single cell omic datasets

The uploaded files are source datasets for the scMTNI algorithm. scMTNI is a multi-task learning framework that integrates the cell lineage structure, scRNA-seq and scATAC-seq measurements to enable joint inference of cell type-specific GRNs. See more details at Preprint: https://biorxiv.org/cgi/content/short/2022.07.25.501350v1. The source data scMTNI_sourcedata.tar.gz contain the following 3 parts: 1) The cluster-specific scRNA-seq matrices and the prior networks for all three datasets and scMTNI inferred consensus networks. 2) Gold standard human and mouse datasets for evaluation. 3) Source data for scMTNI figures 2-8 and supplementary figures. The key for each figure and its corresponding file path is in SourceData_Key_v2.xlsx. The source data Buenrostro_Hematopoiesis.tar.gz contains the scRNA-seq data for human hematopoietic differentiation downloaded from Data S2 of Buenrostro et al.上传的文件为scMTNI算法的源数据集。scMTNI是一款整合细胞谱系结构、单细胞RNA测序（single-cell RNA sequencing, scRNA-seq）与单细胞转座酶可及性测序（single-cell assay for transposase-accessible chromatin sequencing, scATAC-seq）检测数据的多任务学习框架，可实现细胞类型特异性基因调控网络（Gene Regulatory Networks, GRNs）的联合推断。更多详细信息可参见预印本：https://biorxiv.org/cgi/content/short/2022.07.25.501350v1。 源数据集scMTNI_sourcedata.tar.gz包含以下三部分：1）全部三个数据集的聚类特异性scRNA-seq矩阵、先验网络，以及scMTNI推断得到的一致性网络；2）用于评估的金标准人类与小鼠数据集；3）scMTNI相关论文图2至图8及补充图的源数据。每张图的检索密钥及其对应文件路径均收录于SourceData_Key_v2.xlsx中。 源数据集Buenrostro_Hematopoiesis.tar.gz包含从Buenrostro等人的补充数据S2中下载的人类造血分化过程scRNA-seq数据。