SCODA is a web-based, fully automated, all-in-one analysis pipeline for single-cell RNA-seq data.

Discover the Hidden Secrets in Your Single-Cell Transcriptomics data with Our Cutting-Edge Analysis pipeline

Simply upload your single-cell RNA-seq datasets in a compressed file
you will get the results in an AnnData formatted h5ad file
which can be loaded in Python or R to visualize and interact with your analysis results.

The results include

1. Cell-type annotation in 3-level taxonomy, i.e., major-type, minor-type and subset, using HiCAT (MIT license)
2. CNV estimates and tumor cell annotation using InferCNVpy (BSD 3-clause)
3. cell-cell interaction analysis per-condition and per cell-type using CellPhoneDB (MIT license)
4. Differentially expressed gene (DEG)  analysis results per-condition/cell-type.
5. Gene set analysis (GSA) results per-condition/cell-type using GSEApy (BSD 3-clause)

Once you download the result file, you can load it in the example Jupyter notebook we provide to mine biological implications hidden in your data.
With optional configuration setting, you can tailor the  analysis workflow for your specific needs.

Download/Check pipeline description here.

Quick trial steps:

1. Download an example dataset here.
2. Upload it through the form below.
3. Once it is done, download the result (xxx.tar.gz).
4. Open Jupyter notebook in Google Colab by clicking here.
5. Upload the xxx.tar.gz file and follow the instruction there.