README.md

In keita-iida/ASURATBI: A pipeline especially built for computing several single-cell datasets

ASURATBI

ASURATBI is a repository including ASURAT pipelines for analyzing single-cell and spatial transcriptome datasets.

Vignettes

Below are documents for analyzing several single-cell and spatial transcriptome datasets:

• PBMC 4k from healthy donors (10x Genomics)
• PBMC 6k from healthy donors (10x Genomics)
• PBMCs from control and sepsis donors (Reyes et al., 2020)
• Small cell lung cancer (Stewart et al., 2020)
• Pancreatid ductal adenocarcinoma (Moncada et al., 2020)

Below are supporting information:

• Computations for PBMCs datasets (parameter search, benchmark tests, etc.)
• Miscellaneous (separation index, correlation analysis, etc.)

License

GPL-3

Citation

K. Iida, J. Kondo, J. N. Wibisana, M. Inoue, M. Okada, ASURAT: functional annotation-driven unsupervised clustering of single-cell transcriptomes, Bioinformatics 38(18), 4330-4336 (2022). Link

keita-iida/ASURATBI documentation built on Feb. 16, 2023, 9:37 a.m.