Decoding celltypes spatial transcriptomics using machine learning

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Dnr:

NAISS 2024/22-1039

Type:

NAISS Small Compute

Principal Investigator:

Pengwei Xing

Affiliation:

Uppsala universitet

Start Date:

2024-08-20

End Date:

2025-09-01

Primary Classification:

10203: Bioinformatics (Computational Biology) (applications to be 10610)

Webpage:

Allocation

Klemming at PDC: 500 GiB
Dardel-GPU at PDC: 100 GPU-h/month
Dardel at PDC: 2 x 1000 core-h/month

Abstract

We have sequenced 4 tumor samples with 10x spatial transcriptomics technique to decoding the tumor cells heterogeniety. We are going to use Cell2location to deciphering the cell type population in each spatial location in each sample. The Cell2location is based on machine learning using Pytorch which require the GPU resources.