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Data for dynDeepDRIM evaluation

Name: Data for dynDeepDRIM evaluation
Creator: XU, Yu
Keywords: time-course scRNA-seq datasets

Research datakeyboard_double_arrow_right Dataset 30 Aug 2021Publisher:Zenodo

Authors: XU, Yu;

doi: 10.5281/zenodo.6720690 , 10.5281/zenodo.5335938 , 10.5281/zenodo.5335937

Data for dynDeepDRIM evaluation

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Abstract

The data is for evaluating dynDeepDRIM https://github.com/yuxu-1/dynDeepDRIM and repeating the experiment in the related manuscript. The raw time-course single-cell RNA-seq data are from Gene Expression Omnibus (GEO) and ArrayExpress. Accession numbers: GSE79578 (mESC1), GSE65525 (mESC2), E-MTAB-3929 (hESC1), GSE75748(hESC2), GSE104158 (Mouse brain cortex). The simulation datasets (sim1, sim2, sim3, and sim4) were generated by dyngen, a scRNA-seq data simulator. These gene expression datasets were normalized by sctransform, a scRNA-seq data normalization tool based on negative binomial regression.

Keywords

time-course scRNA-seq datasets

1 Research products, page 1 of 1

dynDeepDRIM: a dynamic deep learning model to infer direct regulatory interactions using time-course single-cell gene expression data
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