Single-cell RNA sequencing (scRNA-seq) identifies cell subpopulations within tissue but
does not capture their spatial distribution nor reveal local networks of intercellular …

Sporadic Parkinson's disease (PD) is a progressive neurodegenerative disease, with a
complex risk structure thought to be influenced by interactions between genetic variants and …

Many spatially resolved transcriptomic technologies do not have single-cell resolution but
measure the average gene expression for each spot from a mixture of cells of potentially …

Inferring single-cell compositions and their contributions to global gene expression changes
from bulk RNA sequencing (RNA-seq) datasets is a major challenge in oncology. Here we …

The mammalian cerebral cortex has an unparalleled diversity of cell types, which are
generated during development through a series of temporally orchestrated events that are …

Many computational methods have been developed to infer cell type proportions from bulk
transcriptomics data. However, an evaluation of the impact of data transformation, pre …

Spatially resolved gene expression profiles are key to understand tissue organization and
function. However, spatial transcriptomics (ST) profiling techniques lack single-cell …

Recent development of spatial transcriptomic technologies has made it possible to
characterize cellular heterogeneity with spatial information. However, the technology often …

Recent advancements in spatial transcriptomic technologies have enabled the
measurement of whole transcriptome profiles with preserved spatial context. However …

Single-cell gene expression (transcriptomics) data are becoming robust and abundant, and
are increasingly used to track organisms along their life-course. This allows investigation …