Welcome to SPIRAL
SPIRAL is an algorithm that relies on a Gaussian statistical model to produce a comprehensive overview of significant processes in single cell RNA-seq, spatial transcriptomics or bulk RNA-seq. SPIRAL detects biological processes by identifying the subset of genes involved and the subset of cells, spots or samples.
Here are examples of SPIRAL output for different data sets:
- Single cell RNA-seq data set of lymphoblastoid cells (Zhang et al. 2019) - SPIRAL results
- Single cell RNA-seq data set of Zebrafish differentiation at 7 time points (Wagner et al. 2018) - SPIRAL results
- Spatial transcriptomics data of a sagittal-posterior section of a mouse brain (10x Genomics) - SPIRAL results
- Spatial transcriptomics data of a normal human prostate (10x Genomics) - SPIRAL results
- Bulk RNA-seq data of human differentiation- samples were taken at days 0 and 7−21 (Mandel-Gutfreund lab, available at GitHub repository) - SPIRAL results
- Bulk RNA-seq data of mouse B-cells that were treated with anti-IgM mAb- 25 time points in the 6 hours post stimulation (Chiang et al. 2020) - SPIRAL results
How to cite?
Hadas Biran, Tamar Hashimshony, Yael Mandel-Gutfreund and Zohar Yakhini. SPIRAL: Significant Process InfeRence Algorithm for single cell RNA-sequencing and spatial transcriptomics. (2022). (in review)