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Spatial transcriptomics National Platform

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The spatio-temporal transcriptome of single cells in their tissue

Presentation

Goal ? A national equipment to identify and characterize the transcriptome of each cell, while keeping its spatial position, in multicellular organisms

Where ? In Lyon, France

How ? Latest developments in spatial transcriptomics, some of which are not commercialized yet, for small to large numbers of transcripts, in intact or sorted cells, in whole organisms or tissue sections, combined with data analysis.

Imaging In Vivo profiling of hundreds of gene
Genomics In vivo transcriptome profiling
Data Analysis Spatial reconstruction, lineage tracing,segmentation, deconvolution and RNA spot detection

 

Equipment

Slide-seq
Slide-seq: Optimal tool to quantify the expression pattern of a large number of transcripts (~5000) with a high spatial resolution (3-10 μm) on tissue sections.
Spatial scRNAseq
Optimized tool for transcriptome analysis of a large number of individual cells based on a large spectrum of fluorophores, with excellent sensitivity, resolution, and speed. Spatiotemporal context is computationally reconstructed a posteriori.
smFISH
smFISH: State-of-the-art tool for the precise quantification at a very high spatial resolution of a small (1-10) to large (10-10000) number of transcripts. Compatible with the study of whole-mount samples.
Data analysis
Data analysis: Cutting-edge computational infrastructure and software innovations for image analysis (segmentation, deconvolution, and RNA spot detection) and bioinformatics (spatial reconstruction, lineage tracing).

Next Spatial-Cell-ID seminars

 Read more
12
Jun
2023
Meeting
First Spatial-Cell-ID workshop
 
29
Mar
2023
Meeting
2023 Spatial-Cell-ID Day
 
12
Jan
2022
Meeting
Kick-off meeting
 

News

 Read more

Friday 10 February, 2023

Kick-off vignette
2023 Spatial-Cell-ID meeting on March 29
""
10th Anniversary IGFL Symposium

Wednesday 02 February, 2022

Kick-off vignette
Job offer: Bioinformatician/Computational Biologist in Spatial Transcriptomics

Twitter

Tweets by @Spatial_Cell_ID

Pubmed

Read more
It is better to light a candle than to curse the darkness: single-cell transcriptomics sheds new light on pancreas biology and disease
Visualization of RNA Transcripts in Muscle Stem Cells Using Single-Molecule Fluorescence In Situ Hybridization
Digital spatial profiling of human parathyroid tumors reveals cellular and molecular alterations linked to vitamin D deficiency
SMASH: Scalable Method for Analyzing Spatial Heterogeneity of genes in spatial transcriptomics data
Dimension-agnostic and granularity-based spatially variable gene identification

Contact


SPATIAL-CELL-ID

ENS de Lyon
15 parvis René Descartes
BP 7000
69342 Lyon Cedex 07
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