SampleExplorer: using language models to discover relevant transcriptome data.

Motivation: Over the last two decades, transcriptomics has become a standard technique in biomedical research. We now have large databases of RNA-seq data, accompanied by valuable metadata detailing scientific objectives and the experimental procedures used. The metadata is crucial in understanding and replicating published studies, but so far has been underutilized in helping researchers to discover existing datasets.

Coupling of response biomarkers between tumor and peripheral blood in patients undergoing chemoimmunotherapy.

Platinum-based chemotherapy in combination with anti-PD-L1 antibodies has shown promising results in mesothelioma. However, the immunological mechanisms underlying its efficacy are not well understood and there are no predictive biomarkers to guide treatment decisions. Here, we combine time course RNA sequencing (RNA-seq) of peripheral blood mononuclear cells with pre-treatment tumor transcriptome data from the single-arm, phase 2 DREAM trial (N = 54).

Mining single-cell data for cell type-disease associations.

A robust understanding of the cellular mechanisms underlying diseases sets the foundation for the effective design of drugs and other interventions. The wealth of existing single-cell atlases offers the opportunity to uncover high-resolution information on expression patterns across various cell types and time points. To better understand the associations between cell types and diseases, we leveraged previously developed tools to construct a standardized analysis pipeline and systematically explored associations across four single-cell datasets, spanning a range of tissue types, cell types and developmental time periods.

Identifying SETBP1 haploinsufficiency molecular pathways to improve patient diagnosis using induced pluripotent stem cells and neural disease modelling.

Background: SETBP1 Haploinsufficiency Disorder (SETBP1-HD) is characterised by mild to moderate intellectual disability, speech and language impairment, mild motor developmental delay, behavioural issues, hypotonia, mild facial dysmorphisms, and vision impairment. Despite a clear link between SETBP1 mutations and neurodevelopmental disorders the precise role of SETBP1 in neural development remains elusive. We investigate the functional effects of three SETBP1 genetic variants including two pathogenic mutations p.