Summary
Publication

Title: Slide-seq: A scalable technology for measuring genome-wide expression at high spatial resolution

Authors: Samuel G Rodriques, Robert R Stickels, Aleksandrina Goeva, Carly A Martin, Evan Murray, Charles R Vanderburg, Joshua Welch, Linlin M Chen, Fei Chen, Evan Z Macosko

Date published: 3/29/19

Date added: 5/1/22

Journal: Science

DOI: 10.1126/science.aaw1219

Protocol: Slide-seq

Data source: SCP354

Study design

Species: mouse

Number of samples: 106

Region: Whole brain, hippocampus

Figure: High-resolution RNA capture from tissue by Slide-seq.

Spot-level data

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Sample raw name:

Total spots in the plot: 582

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Gene expression

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Spatially variable genes

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Foldchange direction:
Differential expression (DE) / Gene set enrichment

Sample:

Note: The MAST package were used to calculate DEGs on normalized gene expression data (parameter: log2FC > 0.25, adj.p-value < 0.05).

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0.5

Adjusted p-value cutoff:

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DE direction:
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