Requirments

1. Data Required
   • Genome file
     • Arabidopsis (Genome: TAIR10, GTF: Araport11)
   • Raw data 10x data can be downloaded at CNCB data base
2. Softwares Required
   • CellRanger (Used for processing 10x raw data)
   • scanpy (Used for downstream analysis of 10X data)
   • Seurat (Used for downstream analysis of 10X data)
   • scDblFinder (Used for removing putative doublets)
   • SCTransform (Used to implement 10X data normalization)
   • harmonypy (Used to implement 10X data integration)
   • stereopy (Used for downstream analysis of stereoseq data)
   • metacycle (Used to identify circadian genes)
   • AUCell (Used for calculating gene set expression score)
   • pyscenic (Used for calculating gene set expression score)
   • jpy_tools (A wrapper of single-cell analysis tools, which is available here jpy_tools)
   • rpy2 (Used to implement invocation of R packages in python environment)
   • pygsea (Used to perform GO enrichmenth analysis)

Main steps

Preprocessing

1. Get 10X cell-gene matrix using Cell Ranger

Analysis

These jupyter files contains the scripts needed for downstream analysis. Github often fails to preview large jupyter files, so you can preview these files using nbviewer.

Others

• The gene expression pattern can be explored at our website
  • If you found any bugs in our website, please reported here

Notes

All notebooks share the same jupyter kernel.