10x Single-cell RNA sequencing (scRNA-seq) data from the study of retinal regeneration which is accessible in Science https://science.sciencemag.org/content/370/6519/eabb8598.
Hoang T, Wang J, Boyd P, et al. Gene regulatory networks controlling vertebrate retinal regeneration. Science 2020; 370(6519):eabb8598.
The table 'Sample_information_for_scRNAseq.xlsx' contains treatment and sample information for scRNAseq. Please check this table for the control (or undamaged) samples which are included in scRNA-seq data from each treatment.
The files 'Zebrafish_gene_features.tsv', 'Mouse_gene_features.tsv' and 'Chick_gene_features.tsv' separately contain the features of genes in zebrafish, mouse and chick.
The file 'Zebrafish_development_gene_features.tsv' contains the features of genes which are specifically used for zebrafish retinal development.
The files 'Zebrafish_NMDA_cell_features.tsv', 'Zebrafish_LD_cell_features.tsv', 'Zebrafish_TNFa_cell_features.tsv' and 'Zebrafish_development_cell_features.tsv' contain the features of cells in zebrafish from NMDA treatment, light damage, T+R treatment and retinal development, respectively.
The files 'Mouse_NMDA_cell_features.tsv' and 'Mouse_LD_cell_features.tsv' contain the features of genes and cells in mouse from NMDA treatment and light damage, respectively.
The file 'Chick_NMDAandGF_cell_features.tsv' contains the features of cells in chick NMDA or growth factor treatment.
4. Raw data are available in http://bioinfo.wilmer.jhu.edu/jiewang/scRNAseq/
The folder 'Bam_files' contains raw sequencing data in bam format.
The folder 'Count_matrix' contains the matrix of raw counts in mtx format.
The folder 'Seurat_objects' contains corresponding Seurat objects (the variable 'pbmc'). Please install R package Seurat version 2.3.0 for loading these objects (the instruction is here https://satijalab.org/seurat/install.html).
If the Seurat object can not be loaded in your platform, please try to use the matched 'features of genes', 'features of cells' and 'the matrix of raw counts' to generate a new Seurat object. We strongly suggest you use three matrices to generate your own Seurat object for each condition.
R package IReNA is accessible in https://github.com/jiang-junyao/IReNA.