Dr Julia Steinberg

Postdoctoral Fellow


This person is a member of Sanger Institute Alumni.

Julia focuses on gaining insights into complex human diseases, particularly the underlying biological pathways and networks. She works on integrative approaches at the forefront of high-throughput multi-omics data, combining genetics, methylation, transcription, and proteomics datasets. Julia both develops new methods and applies them to disease data.

Human diseases have a strong burden on both affected individuals and society as a whole. Many of these diseases have a strong genomic component, which can be used to improve the understanding of the disease, leading to better prevention, diagnosis, and treatment.

Consequently, my aim is to uncover the genetic and genomic contribution to a range of human disorders. To this end, I combine a variety of datasets and techniques:

  • I use genetic sequencing data to identify genetic variants that are associated with complex human traits. In particular, isolated populations can be used to identify rare variants that have risen to higher frequency and are possibly under selection. Consequently, I am looking into associations with haematological traits in Greek and Ugandan isolated populations.
  • I apply gene-set and network association approaches for genetic data (from single nucleotide to copy number variants) to uncover the biological processes that contribute to the disease aetiology. For example, I have developed an approach to test whether affected individuals have an accumulation of gene disruptions in a given pathway, and applied this successfully to autism (see publications below).
  • I analyse and combine methylation, gene expression, and proteomics data to understand the differences between disease and intact tissue samples within individuals or between individuals. This can identify convergence on both gene and gene-set level. For example, I have found strong convergence of gene-sets associated with knee osteoarthritis based on the three -omics data types (publication forthcoming). Further work on hip osteoarthritis is in progress.

In the future, I aim to further work on large-scale genetic and genomic data. In particular, the growth of biobanks and electronic health records will offer an unprecedented volume of phenotype and multi-omics data with high granularity. Therefore, integrative methods will be central to maximise the insights and thus health benefits of genetics and genomics.

My timeline


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