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SPIRAL: Significant Process InfeRence Algorithm for single cell RNA-sequencing and spatial transcriptomics

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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.




SPIRAL output for different data sets

Single cell RNA-seq data set of Zebrafish differentiation at 7 time points

link to paper

Spatial transcriptomics data of a sagittal-posterior section of a mouse brain

link to data

Spatial gene expression data set of a mouse brain

Visium CytAssist Gene Expression Libraries of Post-Xenium Mouse Brain (FF)

link to data

Bulk RNA-seq data of human differentiation

Samples were taken at days 0 and 7−21

link to data

Single cell RNA-seq data set of lymphoblastoid cells

link to paper

Spatial transcriptomics data of a normal human prostate

link to data

Bulk RNA-seq data of mouse B-cells that were treated with anti-IgM mAb

25 time points in the 6 hours post stimulation

link to paper

Spatial gene expression data set of human colon cancer

Visium CytAssist Gene Expression Libraries of Post-Xenium Human Colon Cancer (FFPE)

link to data

Single cell RNA-seq data set of Arapidopsis root

link to paper

Single cell RNA-seq data set of aging Drosophila brain

link to paper




How to use SPIRAL?

               



How to cite?

Biran, Hadas, Tamar Hashimshony, Tamar Lahav, Or Efrat, Yael Mandel-Gutfreund, and Zohar Yakhini. "Detecting significant expression patterns in single-cell and spatial transcriptomics with a flexible computational approach." Scientific Reports 14, no. 1 (2024): 26121.

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