SUPR
Single-Cell Copy Number data
Dnr:

NAISS 2023/5-290

Type:

NAISS Medium Compute

Principal Investigator:

Jens Lagergren

Affiliation:

Kungliga Tekniska högskolan

Start Date:

2023-09-01

End Date:

2024-09-01

Primary Classification:

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

Secondary Classification:

10201: Computer Sciences

Allocation

Abstract

In this project we are developing and testing a method for clustering single cell copy number data and also calling the copy number of the cells. The method is based on a probabilistic model which is a non standard mixture of HMM suing the so-called Dirichlet process. The inference is performed using Variational Inference. We are currently working on improving the running time as well as evaluations the accuracy on several types of biological sequence data in particular DLP-data, which we have received from our collaborators at UBC.