Tutorials

CALISTA is a numerically efficient and highly scalable toolbox for an end-to-end analysis of single-cell transcriptomic profiles.

CALISTA includes four essential single-cell analyses for cell differentiation studies, including:

1- single-cell clustering;

2- reconstruction of cell lineage specification;

3- transition gene identification;

4- cell pseudotime ordering.

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In the following tutorials, we describe the main steps of CALISTA (R VERSION) applied to publicly available single-cell gene expression data. 

The current version of CALISTA-R supports data from RT-qPCR and plate-based RNA-seq experiments. For Drop-seq data (working in progress) please refer to CALISTA-MATLAB.

bargaje.png

scRT-qPCR

~2000 cells

Bargaje et al.

moignard.png

scRT-qPCR

~600 cells

Moignard et al.

treutlein.png

scRNA-seq

~400 cells

Treutlein et al.

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scRNA-seq

~760 cells

Chu et al.

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scRT-qPCR

~600 cells

No time info

Moignard et al.

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scRT-qPCR

~600 cells

User-defined cluster assignments

Moignard et al.

© 2018 by Rudiyanto Gunawan