Taiji is an integrative analysis pipeline for analyzing bulk/single-cell ATAC-seq and RNA-seq data. Please go to this website for documentation and tutorials.

• Joint analysis of ATAC-seq, RNA-seq and Hi-C datasets.
• Integrate multiple single cell datasets, scale to more than 1 million cells!

The design philosophy of the Taiji pipeline is focused on:

• Correctness: We only include reliable algorithms and make every effort to ensure the implementations are bug-free.
• Performance: We code algorithms from scratch when necessary to ensure the pipeline can scale to large datasets (thousands of samples at least).
• Convinence: Most analyses have multipe entry points, e.g., Fastq, Bam or Bed. The execution of the pipeline requires only a single command.

We achieve these at the expense of customization. This will be improved in the future.

Pre-built binaries are available for macOS and Linux system:

• taiji-CentOS-x86_64: for Red Hat Enterprise Linux derivatives.

• taiji-Ubuntu-x86_64: for Debian linux derivatives.

• taiji-macOS-XX-XX: for macOS.

Example:

curl -L https://github.com/Taiji-pipeline/Taiji/releases/latest/download/taiji-CentOS-x86_64 -o taiji
chmod +x taiji
./taiji --help

If you have used Taiji in your research, please consider citing the following paper:

K. Zhang, M. Wang, Y. Zhao, W. Wang, Taiji: System-level identification of key transcription factors reveals transcriptional waves in mouse embryonic development. Sci. Adv. 5, eaav3262 (2019).