Single-cell Research
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Spatial Isoform Transcriptomics (SiT): spatial landscape of gene expression isoforms in tissue sections
Current high throughput scRNA-seq technologies, including spatial transcriptomics, rely on 3’ short-read sequencing to identify… read more
Wilko Duprez8 Apr 2021 -
Spatial Transcriptomics: 3 visualization methods to interact with your in situ imaging data.
The introduction of multiplexing in cellular imaging enabled the identification and spatial localization of thousands… read more
Wilko Duprez25 Mar 2021 -
Spatial Transcriptomics: 5 tools to visualize your scRNA-seq data
Adding to the existing complexity of single-cell resolution datasets, the spatial dimension also presents… read more
Wilko Duprez18 Mar 2021 -
Spatially Resolved Single-Cell Data in 2021: where are we?
The terms “spatial” or “spatially-resolved data” have been increasingly thrown around in the field of… read more
Wilko Duprez11 Mar 2021 -
Using Spatial Transcriptomics to map an entire adult mouse brain
Source: Ortiz et al., Molecular atlas of the adult mouse brain, Science Advances 26 Jun… read more
Wilko Duprez18 Feb 2021 -
Taking the leap into single-cell bioinformatics
When I began dabbling into single-cell RNA sequencing (scRNA-seq), the field was just emerging… read more
Denise Gay28 Jan 2021 -
Collaborating for optimal scRNA-seq bioinformatic analysis
Dr. Marc Beyer agreed to meet us to discuss his journey and the best collaborations… read more
Wilko Duprez21 Jan 2021 -
scRNA-seq: artifacts from sample preparation
Independently of the ScRNA-seq methodology you plan to use, there are genetic artifacts bound to… read more
Wilko Duprez7 Jan 2021 -
Cell sample size vs sequencing depth: find your compromise.
With newer technologies enabling the screening of an ever-higher number of cells at a cheaper… read more
Wilko Duprez3 Nov 2020