Stop Thinking and Start Doing. The best learning is practicing!
纸上得来终觉浅，绝知此事要躬行。
Omics data visualizer
CELLXGENE by CZI (Large collection of single-cell omics datasets)
Kidney browser by KPMP (Kidney Precision Medicine Project)
Humphreyslab K.I.T. (WashU) (Collection of kidney single-cell and spatial omics data)
Susztaklab Kidney Biobank (UPenn) (Collection of kidney genomics and single-cell data)
McMahonlab mouse kidney (USC) (Sex, lineage, and regional difference)
Human AKI (Hannover)
Microdissected Rat Kidney Tubule Segments (NIH) (Bulk RNA-seq)
Nephroseq (U-M) (Bulk assays)
MCA (mouse cell atlas)
Single Cell Portal (Broad)
Single-cell and spatial sequencing data analysis
Scanpy (Single-cell and spatial analysis in Python)
Seurat (Single-cell and spatial analysis in R)
Azimuth (Single-cell reference mapping)
SnapATAC2 (snATAC-seq analysis in Python)
Signac (snATAC-seq analysis in R)
MALDIpy (Metabolomics data analysis in Python)
SingleCellWorkshop (by Dr. Gosik)
SeuratDisk (conversion between Seurat and AnnData)
Which single-cell analysis tool is best? (Nature 2022 TECHNOLOGY FEATURE)
Useful resources
Suggested software for PC users (personal opinion): WinSCP or Cyberduck (SFTP/FTP client), PuTTY (SSH client), Sublime (code editing).
ENA (convenient for raw data downloading)
Gene Ontology
WashU Epigenome Browser (Genomic data visulization)
UCSC Genome Browser (Genomic data visulization)
Course | Genomic Data Visualization (Dr. Fan @JHU)
Heng Li’s tools (Genomics)
ImageGP (For beginners: data analysis without informatics experience)
Disclaimer: The team has no conflicts of interest with the vendors/laboratories.