Jesper Bäckdahl§, Lovisa Franzén§, Lucas Massier, Qian Li, Jutta Jalkanen, Hui Gao, Alma Andersson, Nayanika Bhalla, Anders Thorell, Mikael Rydén§, Patrik L. Ståhl§, Niklas Mejhert§

§ These authors contributed equally to the work.

This repo contains all R code and smaller tables related to the publication by Bäckdahl J & Franzén L, et al (2021).

In this project, we performed spatial transcriptomics, using the 10x Genomic's Visium platform, on abdominal subcutaneous white adipose tissue (scWAT) to generate data from a total of ten human subjects. The subjects are of a range of different ages and with different body mass index (BMI). Four of the subjects were subjected to euglycemic hyperinsulinemic clamp with samples collected before and after – the data from these samples were used in the "insulin" analyses.

Publication: Bäckdahl et al., "Spatial mapping reveals human adipocyte subpopulations with distinct sensitivities to insulin", Cell Metabolism, 10 Augusti 2021 (online), DOI:10.1016/j.cmet.2021.07.018

• data
  • visium
    • Download data from Mendeley Data (DOI: 10.17632/3bs5f8mvbs.1) and place in this folder
  • gene_annotation: two tables with gene annotation information used for gene filtering and ID conversions
  • CAGE: Data containing FANTOM5 CAGE bulk data used for comparison (Rydén et al., 2016, DOI: 10.1016/j.celrep.2016.07.070)
• scripts: All main R scripts used for processing and analysing the Visium data
• image_analysis_lm: R code, ImageJ macro, and final data output related to the adipocyte size determination using image analysis
• doc: Contains html output reports, pdf with data analysis overview flowchart, and other documents

This project is licensed under the terms of the MIT license.

For questions related to the Visium data and related code, please contact Lovisa Franzén ([email protected])

For questions related to the image analysis and adipocyte size determination, please contact Lucas Massier ([email protected])