Expanding a Nextflow pipeline for single-cell data

Project Description

The epigenome is the layer on top of the genome that regulates how genes are expressed. We developed a Nextflow pipeline that uses machine learning models, that were trained to predict gene expression from epigenome data, to find genes which are associated with specific conditions such as cancer. The current implementation works entirely on bulk data.

Research Goals

• Adjust and expand the HAWAS pipeline to also allow the usage of single-cell data.
• Add input processing of single-cell data, which can then be given to pre-trained single-cell models.
• Test the pipeline on additional data.

Prerequisites

• Python/R programming
• Ideally some knowledge about epigenomics
• Experience with Nextflow would help but not necessary

How to Apply

Send a short Email with a short motivation to the corresponding supervisor l.rumpf|em.uni-frankfurt.de.