Spatial Omics Data Analysis

spatial_omics_data_analysis.jpg

 

 29th Aug - 02nd Sept 2022

 Online (Zoom)

 

📹 Recording of the course

https://www.youtube.com/playlist?list=PLBsJUKzoJTHSfWrLhCPCN-_vVU-klEi6p

Course staff

Paulo Czarnewski (Course Leader)

Christophe Avenel (Course Leader)

Lars Borm

Carolina Wählby

Giovanni Palla

Naveed Ishaque

Anna Shaar

David Fischer

Hanna Spitzer

Sergio Sallas

Åsa Björklund

Sebastian Tiesmeyer

Ludvig Bergenstråle

Eduard Chelebian

 

Contact: edu.spatial@nbis.se

 

 

Covered content

  • Hands-on experience with ST (Visium), ISS, scRNAseq data analysis

  • Fluorescence-based image formats, standards and quality control

  • Image alignment, registration and ISS decoding

  • Nuclei-based and segmentation-free cell identification

  • Data imputation using ISS and single cell datasets

  • Analysis of Spatial Transcriptomics dataset

  • Cell-type deconvolution (ST and single cell)

  • Cell-cell and ligand-receptor interaction analysis

  • Mapping of multiple spatial data to a common reference

  • High-resolution projection of gene expression to H&E images

  • Interactive visualisation of spatial omics data

 

 

Applications

Application open: 2022-05-20

Application deadline: 2022-07-31

Application form: https://forms.gle/Gu2GJwsPhbpAE8RV9

Course fee: This course is free of charge.

Please note that NBIS training events do not provide any formal university credits. The training content is estimated to correspond to a certain number of credits, however the estimated credits are just guidelines. If formal credits are crucial, the student needs to confer with the home department before submitting a course application in order to establish whether the course is valid for formal credits or not.

Practical exercises will be performed using either R or Python, so we only accept students that fulfil the entry requirements below.

 

Entry requirements:

  • Basic knowledge in Python

  • Be able to use your own computer with a web camera

  • Have miniconda3 installed in your computer 
  • Desirable: Previous experience with single cell RNA-seq analysis is an advantage.

  • If we receive more applications, participants will be selected based on several criteria. Selection criteria include correct entry requirements, motivation to attend the course as well as gender and geographical balance.

     

 

Schedule
The Schedule can be found here:
https://uppsala.instructure.com/courses/58516/pages/schedule

 

Exercises
TBA

 

Precourse material
The Schedule can be found here:

https://uppsala.instructure.com/courses/58516/pages/introduction-to-pre-course?module_item_id=522573

 

 

 

CC attribution share alike This course content is offered under a CC attribution share alike license. Content in this course can be considered under this license unless otherwise noted.